DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This communication is in response to the Application Filed on 10/22/2024.
Claims 1-19 are pending in this application.
Drawings
The drawing(s) filed on 10/22/2024 are accepted by the Examiner.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/22/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, and opinion). The independent claim(s) 1, 7, and 14 recite(s) a method for object recognition and a non-transitory computer readable medium for object recognition. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the independent claims 1, 7 and 14 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Independent claims 1 and 7 are directed to a method and claim 14 is directed to an apparatus.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Independent claims 1, 7, and 14 comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding independent claim(s) 1: the limitations recite:
detecting contours from data measurements of one or more objects provided by one or more vision sensors (mental process including observation and evaluation, and can be done mentally in the human mind);
detecting concavities of the contours of the one or more objects (mental process including observation and evaluation, and can be done mentally in the human mind);
evaluating correctness of each of the concavities (mental process including observation and evaluation, and can be done mentally in the human mind);
executing an action for the each of the concavities based on the evaluated correctness to produce revised contours, the action selected from one of keep, complete, or remove (mental process including observation and evaluation, and can be done mentally in the human mind); and
executing an object recognition process on the revised contours (mental process including observation and evaluation, and can be done mentally in the human mind)
Regarding independent claim(s) 7: the limitations recite:
detecting contours from data measurements of one or more objects provided by one or more vision sensors (mental process including observation and evaluation, and can be done mentally in the human mind);
detecting concavities of the contours of the one or more objects (mental process including observation and evaluation, and can be done mentally in the human mind);
evaluating a quality of each of the contours based on associated ones of the concavities (mental process including observation and evaluation, and can be done mentally in the human mind);
executing an object recognition process on the contours (mental process including observation and evaluation, and can be done mentally in the human mind); and
executing an action for each recognized object from the execution of the object recognition based on the quality of ones of the contours associated with the recognized object, the action selected from one of assign for pick-up by a robot or apply slight displacement motion by the robot (mental process including observation and evaluation, and can be done mentally in the human mind)
Regarding independent claim(s) 14: the limitations recite:
detecting contours from data measurements of one or more objects provided by one or more vision sensors (mental process including observation and evaluation, and can be done mentally in the human mind);
detecting concavities of the contours of the one or more objects (mental process including observation and evaluation, and can be done mentally in the human mind);
evaluating correctness of each of the concavities (mental process including observation and evaluation, and can be done mentally in the human mind);
executing an action for the each of the concavities based on the evaluated correctness to produce revised contours, the action selected from one of keep, complete, or remove (mental process including observation and evaluation, and can be done mentally in the human mind); and
executing an object recognition process on the revised contours (mental process including observation and evaluation, and can be done mentally in the human mind)
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person could mentally observe an outline of an object and concavities in the outline, decide whether the outline seems correct and whether to fix the outline to be able to accurately recognize the correct object, and decide whether an action will be assigned out. The mere nominal recitation that the various steps are being executed by a non-transitory computer readable medium does not take the limitations out of the mental process grouping. Thus, the claims recite a mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Independent claims 1, 7, and 14 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Independent claims 14 discloses a non-transitory computer-readable storage medium, which are generic computer components and/or insignificant pre/post-solution extra activity that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea in a method.
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Independent claim(s) 1, 7, and 14 do not recite any additional elements that are not well-understood, routine or conventional. The use of a generic computer elements are routine, well-understood and conventional process that is performed by computers.
Thus, since independent claims 1, 7, and 14 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that independent claims 1, 7, and 14 are not eligible subject matter under 35 U.S.C 101.
Regarding claim 2: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 3: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the correctness of the each of the concavities is based on a ratio of the each of the concavity to a side length of a bounding rectangle of an associated contour exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 4: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein complete is selected as the action when each of the concavities is longer than a preset threshold and evaluated as incorrect are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 5: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein complete is selected as the action for the each of the concavity evaluated as incorrect when depth information between the one or more objects and the one or more vision sensors indicates that a depth difference in an area proximate to the each of the concavities exceeds a threshold; and wherein remove is selected as the action for the each of the concavities evaluated as incorrect when the depth difference does not exceed the threshold. are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 6: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein remove is selected as the action for the each of the concavities evaluated as incorrect when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects; wherein complete is selected as the action for the each of the concavities evaluated as incorrect when the each of the concavity associated with the first contour also occurs in the second contour are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 8: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 9: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the quality of the each of the contours is based on an average or median concavity of the each of the contours exceeding a threshold are mental processes including mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 10: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the quality of the each of the contours is based on maximum concavity of the each of the contours exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 11: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the assign for pick-up by the robot is selected as the action when an associated contour of the recognized object is evaluated as having the quality above a threshold, or for when detected concavities on the associated contour are maintained are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 12: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the apply slight displacement motion by the robot is selected as the action for when an associated contour of the recognized object is evaluated as having a quality below a threshold, or for when at least one concavity is completed or removed from the associated contour are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 13: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): updating statistics for the object recognition process based on one or more of a number of the one or more objects having the quality exceeding a threshold, an average concavity of the one or more objects having the quality lower than the threshold, a median concavity of the one or more objects having the quality lower than the threshold, and a maximum concavity of the one or more objects having the quality lower than the threshold. are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 15: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 16: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the evaluating the correctness of the each of the concavities is based on a ratio of the each of the concavity to a side length of a bounding rectangle of an associated contour exceeding a threshold are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind and mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations.
Regarding claim 17: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein complete is selected as the action when each of the concavities is longer than a preset threshold and evaluated as incorrect are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 18: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein complete is selected as the action for the each of the concavity evaluated as incorrect when depth information between the one or more objects and the one or more vision sensors indicates that a depth difference in an area proximate to the each of the concavities exceeds a threshold; and wherein remove is selected as the action for the each of the concavities evaluated as incorrect when the depth difference does not exceed the threshold. are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Regarding claim 19: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein remove is selected as the action for the each of the concavities evaluated as incorrect when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects; wherein complete is selected as the action for the each of the concavities evaluated as incorrect when the each of the concavity associated with the first contour also occurs in the second contour are mental processes including mental process including observation and evaluation, and can be done mentally in the human mind.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1 and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yu et al. (US 10,614,340 B1, hereinafter, “Yu”).
Regarding claim 1, Yu discloses a method for an object recognition system (See Yu, Col. 27, lines 3-5, Returning to FIG. 3, the method 300 further includes an operation 310, in which the processing circuit 110 of the computing system employs 101 performs object recognition; Fig. 1D), comprising:
detecting contours (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects) from data measurements of one or more objects (See Yu, Col. 2, lines 2-4, the spatial structure data may describe a structure of one or more objects) provided by one or more vision sensors (See Yu, Col. 7, lines 56-57, the spatial structure sensing device 151 is a camera having an image sensor);
detecting concavities (See Yu, Col. 22, lines 26-28, if only one quadrant contains part of the shape, the vertex may be determined to be concave; Col. 2, lines 58-60, The vertices may be points that describe a contour of the layer, and thus may also be referred to as contour points) of the contours of the one or more objects (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects);
evaluating correctness of each of the concavities (See Yu, Col. 17, lines 65-57 and Col. 28, line 1, In some cases, the detection hypothesis may be modified and refined, and the convex corners may provide a starting point for determining a correct detection hypothesis. Examiner considers determining a correct detection hypothesis as evaluating correctness);
executing an action for the each of the concavities based on the evaluated correctness to produce revised contours, the action selected from one of keep, complete, or remove (See Yu, Col. 28, lines 5-9, In an embodiment, operation 310 may involve determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect. Examiner considers filter out or ignore as actions to be taken) and
executing an object recognition process on the revised contours (See Yu, Col. 28, lines 15-16, the detection hypothesis may be filtered or otherwise ignored for purposes of object recognition. Examiner considers the detection hypothesis to be the revised contour on which an object recognition process will be executed on).
Regarding claim 14, Yu discloses a non-transitory computer readable medium, storing instructions for an object recognition system, the instructions (See Yu, Col. 9, lines 37-43, In certain cases, the non-transitory computer-readable medium 120 further stores computer readable program instructions that, when executed by the processing circuit 110, causes the processing circuit 110 to perform one or more methodologies described here, such as the operation described with respect to FIG. 3; Fig. 2A - element 101 and 120); comprising:
detecting contours (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects) from data measurements of one or more objects (See Yu, Col. 2, lines 2-4, the spatial structure data may describe a structure of one or more objects) provided by one or more vision sensors (See Yu, Col. 7, lines 56-57, the spatial structure sensing device 151 is a camera having an image sensor);
detecting concavities (See Yu, Col. 22, lines 26-28, if only one quadrant contains part of the shape, the vertex may be determined to be concave; Col. 2, lines 58-60, The vertices may be points that describe a contour of the layer, and thus may also be referred to as contour points) of the contours of the one or more objects (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects);
evaluating correctness of each of the concavities (See Yu, Col. 17, lines 65-57 and Col. 28, line 1, In some cases, the detection hypothesis may be modified and refined, and the convex corners may provide a starting point for determining a correct detection hypothesis. Examiner considers determining a correct detection hypothesis as evaluating correctness);
executing an action for the each of the concavities based on the evaluated correctness to produce revised contours, the action selected from one of keep, complete, or remove (See Yu, Col. 28, lines 5-9, In an embodiment, operation 310 may involve determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect. Examiner considers filter out or ignore as actions to be taken); and
executing an object recognition process on the revised contours (See Yu, Col. 28, lines 15-16, the detection hypothesis may be filtered or otherwise ignored for purposes of object recognition. Examiner considers the detection hypothesis to be the revised contour on which an object recognition process will be executed on).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 2, 3, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Ushijima (US 2013/0004019 A1, hereinafter, “Ushijima”).
Regarding claim 2, in which claim 1 is incorporated, Yu does not disclose wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold.
Ushijima teaches wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities (See Ushijima,¶ [0065] Specifically, the depressed portion determination unit 65 sets parameters, including a maximum of contour line lengths (lcmax) between contour points and corresponding opposite contour points) and a convex hull of the contour (See Ushijima, ¶ [0036] a contour line 311 that extends between the pixels 301 and 302. Examiner considers the contour line connecting all pixels as the convex hull) exceeding a threshold (See Ushijima, ¶ [[0068] After that, at Step S105, the depressed portion determination unit 65 determines whether or not the maximum of the contour line lengths (lcmax) exceeds a predetermined threshold (Th1)).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold based on the method of Ushijima’s reference. The suggestion/motivation would have been to determine, based on a length of the first shortcut line or a length of a first route that extends along the contour line between the first and second contour points, whether or not a portion surrounded by the first shortcut line and the first route, not contained in the given region, is a depressed portion as suggested by Ushijima in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Ushijima with Yu to obtain the invention as specified in claim 2.
Regarding claim 3, in which claim 1 is incorporated, Yu discloses wherein the evaluating the correctness of the each of the concavities is [based on a ratio of the each of the concavity] to a side length of a bounding rectangle of an associated contour (See Yu, Col. 19, lines 66-67, The second length may be, e.g., a distance from the vertex 512b to the vertex 512c) exceeding a threshold (See Yu, Col. 20, lines 29-32, the threshold length may be selected to eliminate or otherwise filter out vertices of the spatial structure data that form edges which are less than the minimum expected length).
However, Yu does not disclose [wherein the evaluating the correctness of the each of the concavities is] based on a ratio of the each of the concavity [to a side length of a bounding rectangle of an associated contour exceeding a threshold.]
Ushijima teaches [wherein the evaluating the correctness of the each of the concavities is] based on a ratio of the each of the concavity (See Ushijima, ¶ [0079] a ratio of the contour line length between the contour points) [to a side length of a bounding rectangle of an associated contour exceeding a threshold.]
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the correctness of the each of the concavities is based on a ratio of the each of the concavity based on the method of Ushijima’s reference. The suggestion/motivation would have been to determine, based on a length of the first shortcut line or a length of a first route that extends along the contour line between the first and second contour points, whether or not a portion surrounded by the first shortcut line and the first route, not contained in the given region, is a depressed portion as suggested by Ushijima in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Ushijima with Yu to obtain the invention as specified in claim 3.
Regarding claim 15, in which claim 14 is incorporated, Yu does not disclose wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold.
Ushijima teaches wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities (See Ushijima,¶ [0065] Specifically, the depressed portion determination unit 65 sets parameters, including a maximum of contour line lengths (lcmax) between contour points and corresponding opposite contour points) and a convex hull of the contour (See Ushijima, ¶ [0036] a contour line 311 that extends between the pixels 301 and 302) exceeding a threshold (See Ushijima, ¶ [[0068] After that, at Step S105, the depressed portion determination unit 65 determines whether or not the maximum of the contour line lengths (lcmax) exceeds a predetermined threshold (Th1)).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the correctness of the each of the concavities is based on a distance between an extreme point of the each of the concavities and a convex hull of the contour exceeding a threshold based on the method of Ushijima’s reference. The suggestion/motivation would have been to determine, based on a length of the first shortcut line or a length of a first route that extends along the contour line between the first and second contour points, whether or not a portion surrounded by the first shortcut line and the first route, not contained in the given region, is a depressed portion as suggested by Ushijima in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Ushijima with Yu to obtain the invention as specified in claim 15.
Regarding claim 16, in which claim 14 is incorporated, Yu discloses wherein the evaluating the correctness of the each of the concavities is [based on a ratio of the each of the concavity] to a side length of a bounding rectangle of an associated contour (See Yu, Col. 19, lines 66-67, The second length may be, e.g., a distance from the vertex 512b to the vertex 512c) exceeding a threshold (See Yu, Col. 20, lines 29-32, the threshold length may be selected to eliminate or otherwise filter out vertices of the spatial structure data that form edges which are less than the minimum expected length).
However, Yu does not disclose [wherein the evaluating the correctness of the each of the concavities is] based on a ratio of the each of the concavity [to a side length of a bounding rectangle of an associated contour exceeding a threshold.]
Ushijima teaches [wherein the evaluating the correctness of the each of the concavities is] based on a ratio of the each of the concavity (See Ushijima, ¶ [0079] a ratio of the contour line length between the contour points) [to a side length of a bounding rectangle of an associated contour exceeding a threshold.]
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the correctness of the each of the concavities is based on a ratio of the each of the concavity based on the method of Ushijima’s reference. The suggestion/motivation would have been to determine, based on a length of the first shortcut line or a length of a first route that extends along the contour line between the first and second contour points, whether or not a portion surrounded by the first shortcut line and the first route, not contained in the given region, is a depressed portion as suggested by Ushijima in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Ushijima with Yu to obtain the invention as specified in claim 16.
Claims 4 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Liu et al. (CN 112270679 B, hereinafter, “Liu”).
Regarding claim 4, in which claim 1 is incorporated, Yu discloses wherein [complete is selected as the action when each of the concavities is longer than a preset threshold] and evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect).
However, Yu does not disclose wherein complete is selected as the action when each of the concavities is longer than a preset threshold.
Liu teaches wherein complete is selected as the action (See Liu, Pg. 6, lines 1-2, the matched concave points are connected with each other, namely finishing the outline segmentation. Examiner considers finishing the outline segmentation as the action complete) when each of the concavities is longer than a preset threshold (See Liu, Pg. 7, lines 15-16, the convex defect value exceeds the adjacent point of the set threshold to form a concave edge).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein complete is selected as the action when each of the concavities is longer than a preset threshold based on the method of Liu’s reference. The suggestion/motivation would have been to find the matching point in the concave point sequence and the inner profile of the other concave edge as suggested by Liu in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu with Yu to obtain the invention as specified in claim 4.
Regarding claim 17, in which claim 14 is incorporated, Yu discloses wherein [complete is selected as the action when each of the concavities is longer than a preset threshold] and evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect).
However, Yu does not disclose wherein complete is selected as the action when each of the concavities is longer than a preset threshold.
Liu teaches wherein complete is selected as the action (See Liu, Pg. 6, lines 1-2, the matched concave points are connected with each other, namely finishing the outline segmentation. Examiner considers finishing the outline segmentation as the action complete) when each of the concavities is longer than a preset threshold (See Liu, Pg. 7, lines 15-16, the convex defect value exceeds the adjacent point of the set threshold to form a concave edge).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein complete is selected as the action when each of the concavities is longer than a preset threshold based on the method of Liu’s reference. The suggestion/motivation would have been to find the matching point in the concave point sequence and the inner profile of the other concave edge as suggested by Liu in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu with Yu to obtain the invention as specified in claim 17.
Claims 5 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Ushijima (US 2013/0004019 A1, hereinafter, “Ushijima”) and further in view of Liu et al. (CN 112270679 B, hereinafter, “Liu”).
Regarding claim 5, in which claim 1 is incorporated, Yu discloses wherein [complete is selected as the action] for the each of the concavity evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) when depth information between the one or more objects and the one or more vision sensors indicates that a depth difference in an area proximate to the each of the concavities exceeds a threshold (See Yu, Col. 13, lines 45-49, points that are represented by a point cloud (or other form of spatial structure data) may be divided into different layers based on a sharp change in depth value. A change may be considered sharp if, e.g., it has an absolute value or a rate of change that exceeds a defined threshold); and
[wherein remove is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) when the depth difference does not exceed the threshold (See Yu, Col. 13, lines 45-49, points that are represented by a point cloud (or other form of spatial structure data) may be divided into different layers based on a sharp change in depth value. A change may be considered sharp if, e.g., it has an absolute value or a rate of change that exceeds a defined threshold).
However, Yu does not disclose wherein complete is selected as the action and wherein remove is selected as the action.
Liu teaches wherein complete is selected as the action (See Liu, Pg. 6, lines 1-2, the matched concave points are connected with each other, namely finishing the outline segmentation. Examiner considers finish the outline segmentation as the action of complete).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein complete is selected as the action based on the method of Liu’s reference. The suggestion/motivation would have been to find the matching point in the concave point sequence and the inner profile of the other concave edge as suggested by Liu in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
However, Yu and Liu do not teach wherein remove is selected as the action.
Ushijima teaches wherein remove is selected as the action (See Ushijima, ¶ [0078] the contour point 805 and respective two adjacent contour points are removed from the search area).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein remove is selected as the action based on the method of Ushijima’s reference. The suggestion/motivation would have been to extracts, from an image containing a target region, a segment of a boundary of the target region which corresponds to a depressed portion as suggested by Ushijima at ¶ [0006].
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu and Ushijima with Yu to obtain the invention as specified in claim 5.
Regarding claim 18, in which claim 14 is incorporated, Yu discloses wherein [complete is selected as the action] for the each of the concavity evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) when depth information between the one or more objects and the one or more vision sensors indicates that a depth difference in an area proximate to the each of the concavities exceeds a threshold (See Yu, Col. 13, lines 45-49, points that are represented by a point cloud (or other form of spatial structure data) may be divided into different layers based on a sharp change in depth value. A change may be considered sharp if, e.g., it has an absolute value or a rate of change that exceeds a defined threshold); and
[wherein remove is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) when the depth difference does not exceed the threshold (See Yu, Col. 13, lines 45-49, points that are represented by a point cloud (or other form of spatial structure data) may be divided into different layers based on a sharp change in depth value. A change may be considered sharp if, e.g., it has an absolute value or a rate of change that exceeds a defined threshold).
However, Yu does not disclose wherein complete is selected as the action and wherein remove is selected as the action.
Liu teaches wherein complete is selected as the action (See Liu, Pg. 6, lines 1-2, the matched concave points are connected with each other, namely finishing the outline segmentation. Examiner considers finish the outline segmentation as the action of complete).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein complete is selected as the action based on the method of Liu’s reference. The suggestion/motivation would have been to find the matching point in the concave point sequence and the inner profile of the other concave edge as suggested by Liu in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
However, Yu and Liu do not teach wherein remove is selected as the action.
Ushijima teaches wherein remove is selected as the action (See Ushijima, ¶ [0078] the contour point 805 and respective two adjacent contour points are removed from the search area).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference w wherein remove is selected as the action based on the method of Ushijima’s reference. The suggestion/motivation would have been to extracts, from an image containing a target region, a segment of a boundary of the target region which corresponds to a depressed portion as suggested by Ushijima at ¶ [0006].
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu and Ushijima with Yu to obtain the invention as specified in claim 18.
Claims 6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Yano et al. (WO 2013/154062 A1, hereinafter, “Yano).
Regarding claim 6, in which claim 1 is incorporated, Yu discloses [wherein remove is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) [when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects;]
[wherein complete is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) [when the each of the concavity associated with the first contour extracted from the target image data also occurs in the second contour.]
However, Yu does not disclose wherein remove is selected as the action [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects;
wherein complete is selected as the action [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with the first contour extracted from the target image data also occurs in the second contour.
Yano teaches wherein remove is selected as the action (See Yano, Pg. 8, line 4, removing an inappropriate combination of two points) [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with a first contour of an object (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) causes a difference (See Yano, Pg. 8, lines 6-7, an inappropriate combination of two points (inappropriate complementary contour candidates). Examiner considers an inappropriate combination as a difference) between the first contour of the object from the one or more objects (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) and a second contour associated with the object from the one or more objects (See Yano, Pg. 7, line 20, the corrected complementary contour);
wherein complete is selected as the action (See Yano, Pg. 8, line 1, complementing an arbitrary two points with a curve. Examiner considers connecting the two points as completing) [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with the first contour extracted from the target image data (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) extracted from the target image data) also occurs in the second contour (See Yano Pg. 7, lines 19-21, Next, the contour matching unit 105 uses the contour information (silhouette information) extracted from the target image data and the corrected complementary contour to perform object matching processing. Examiner considers the corrected complementary contour as the second contour and the matching processes as evaluation if the first contour occurs in the second contour).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold based on the method of Yano’s reference. The suggestion/motivation would have been to compare contour information using a portion of the contour obtained by dividing the contours extracted from the subject image data on the basis of the selected complementary contours as suggested by Yano in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Yano with Yu to obtain the invention as specified in claim 6.
Regarding claim 19, in which claim 1 is incorporated, Yu discloses [wherein remove is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) [when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects;]
[wherein complete is selected as the action] for the each of the concavities evaluated as incorrect (See Yu, Col. 28, lines 6-9, determining whether to filter out or otherwise ignore a detection hypothesis. More generally speaking, such an embodiment may involve determining whether the detection hypothesis is likely to be incorrect) [when the each of the concavity associated with the first contour extracted from the target image data also occurs in the second contour.]
However, Yu does not disclose wherein remove is selected as the action [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with a first contour of an object causes a difference between the first contour of the object from the one or more objects and a second contour associated with the object from the one or more objects;
wherein complete is selected as the action [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with the first contour extracted from the target image data also occurs in the second contour.
Yano teaches wherein remove is selected as the action (See Yano, Pg. 8, line 4, removing an inappropriate combination of two points) [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with a first contour of an object (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) causes a difference (See Yano, Pg. 8, lines 6-7, an inappropriate combination of two points (inappropriate complementary contour candidates). Examiner considers an inappropriate combination as a difference) between the first contour of the object from the one or more objects (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) and a second contour associated with the object from the one or more objects (See Yano, Pg. 7, line 20, the corrected complementary contour);
wherein complete is selected as the action (See Yano, Pg. 8, line 1, complementing an arbitrary two points with a curve. Examiner considers connecting the two points as completing) [for the each of the concavities evaluated as incorrect] when the each of the concavity associated with the first contour extracted from the target image data (See Yano, Pg. 7, lines 19-20, contour information (silhouette information) extracted from the target image data) also occurs in the second contour (See Yano Pg. 7, lines 19-21, Next, the contour matching unit 105 uses the contour information (silhouette information) extracted from the target image data and the corrected complementary contour to perform object matching processing. Examiner considers the corrected complementary contour as the second contour and the matching processes as evaluation if the first contour occurs in the second contour).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold based on the method of Yano’s reference. The suggestion/motivation would have been to compare contour information using a portion of the contour obtained by dividing the contours extracted from the subject image data on the basis of the selected complementary contours as suggested by Yano in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Yano with Yu to obtain the invention as specified in claim 19.
Claims 7, 11, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Diankov et al. (WO 2022/245842 A1, hereinafter, “Diankov”).
Regarding claim 7, Yu discloses a method for an object recognition system (See Yu, Col. 27, lines 3-5, Returning to FIG. 3, the method 300 further includes an operation 310, in which the processing circuit 110 of the computing system employs 101 performs object recognition; Fig. 1D), comprising:
detecting contours (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects) from data measurements of one or more objects (See Yu, Col. 2, lines 2-4, the spatial structure data may describe a structure of one or more objects) provided by one or more vision sensors (See Yu, Col. 7, lines 56-57, the spatial structure sensing device 151 is a camera having an image sensor);
detecting concavities (See Yu, Col. 22, lines 26-28, if only one quadrant contains part of the shape, the vertex may be determined to be concave; Col. 2, lines 58-60, The vertices may be points that describe a contour of the layer, and thus may also be referred to as contour points) of the contours of the one or more objects (See Yu, Col. 2, lines 37-39, recognition and identification of one or more contours, surfaces, edges, and/or corners of individual objects);
evaluating a quality of each of the contours based on associated ones of the concavities (See Yu, Col. 16, lines 34-39, In such an embodiment, operation 306 may involve (e.g., via object identification manager 206) fitting the set of lines 514a-514f in a manner that best approximates respective locations of the edge points. Examiner considers fitting the set of lines in the best approximate location as evaluating quality).
executing an object recognition process on the contours (See Yu, Col. 27, lines 3-5, the method 300 further includes an operation 310, in which the processing circuit 110 of the computing system employs 101 performs object recognition; Fig. 3 - element 310); and
[executing an action for each recognized object from the execution of the object recognition based on the quality of ones of the contours associated with the recognized object, the action selected from one of assign for pick-up by a robot or apply slight displacement motion by the robot.]
However, Yu does not disclose executing an action for each recognized object from the execution of the object recognition based on the quality of ones of the contours associated with the recognized object, the action selected from one of assign for pick-up by a robot or apply slight displacement motion by the robot.
Diankov teaches executing an action for each recognized object from the execution of the object recognition based on the quality of ones of the contours associated with the recognized object (See Diankov, [00136] After more accurately estimating the dimensions of the target object 3000A, the computing system 1100/3100 may determine whether or not to release and regrasp the object), the action selected from one of assign for pick-up by a robot (See Diankov, ¶ [0023] the robot 1300 may be configured to pick up the containers from one location and move them to another location) or apply slight displacement motion by the robot (See Diankov, [0135] the computing system 1100/3100 would have instructed the robotic arm 3320 of the robot 3300 to drag and not lift the object, reducing the risk of damage).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein executing an action for each recognized object from the execution of the object recognition based on the quality of ones of the contours associated with the recognized object, the action selected from one of assign for pick-up by a robot or apply slight displacement motion by the robot based on the method of Diankov’s reference. The suggestion/motivation would have been to increase the accuracy and efficiency of robotic object handling as suggested by Diankov in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Diankov with Yu to obtain the invention as specified in claim 7.
Regarding claim 11, in which claim 7 is incorporated, Yu does not disclose wherein the assign for pick-up by the robot is selected as the action when an associated contour of the recognized object is evaluated as having the quality above a threshold, or for when detected concavities on the associated contour are maintained.
Diankov teaches wherein the assign for pick-up by the robot is selected as the action (See Diankov, ¶ [0023] the robot 1300 may be configured to pick up the containers from one location and move them to another location) when an associated contour of the recognized object is evaluated as having the quality above a threshold, or for when detected concavities on the associated contour are maintained (See Diankov, ¶ [00117] If the region-candidate ratio is greater than or equal to a certain threshold, the computing system may select the lifting motion).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the assign for pick-up by the robot is selected as the action when an associated contour of the recognized object is evaluated as having the quality above a threshold, or for when detected concavities on the associated contour are maintained based on the method of Diankov’s reference. The suggestion/motivation would have been to increase the accuracy and efficiency of robotic object handling as suggested by Diankov in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Diankov with Yu to obtain the invention as specified in claim 11.
Regarding claim 12, in which claim 7 is incorporated, Yu does not disclose wherein the apply slight displacement motion by the robot is selected as the action for when an associated contour of the recognized object is evaluated as having a quality below a threshold, or for when at least one concavity is completed or removed from the associated contour.
Diankov teaches wherein the apply slight displacement motion by the robot is selected as the action (See Diankov, [0135] the computing system 1100/3100 would have instructed the robotic arm 3320 of the robot 3300 to drag and not lift the object, reducing the risk of damage) for when an associated contour of the recognized object is evaluated as having a quality below a threshold, or for when at least one concavity is completed or removed from the associated contour (See Diankov, ¶ [00118] The computing system 1100/3100 may select the dragging motion because, if the threshold is not surpassed, the certainty that the minimum viable region accurately represents the dimensions of the target object 3000A is lower).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the apply slight displacement motion by the robot is selected as the action for when an associated contour of the recognized object is evaluated as having a quality below a threshold, or for when at least one concavity is completed or removed from the associated contour based on the method of Diankov’s reference. The suggestion/motivation would have been to increase the accuracy and efficiency of robotic object handling as suggested by Diankov in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Diankov with Yu to obtain the invention as specified in claim 12.
Claims 8 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Diankov et al. (WO 2022/245842 A1, hereinafter, “Diankov”) and further in view of Liu et al. (CN 112270679 B, hereinafter, “Liu”).
Regarding claim 8, in which claim 7 is incorporated, Yu does not disclose wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold.
Liu teaches wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold (See Liu, Pg. 3, lines 32-34, then further judging the absolute value of the cross product if it is greater than the set concave point threshold Cth, if it is greater than Cth, then the O point is marked as the concave point of the outline).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the quality of the each of the contours is based on a number of concavities for the each of the contours exceeding a threshold based on the method of Liu’s reference. The suggestion/motivation would have been for the accuracy and speed of the outline dividing technology based on the concave point matching as suggested by Liu at Pg. 2, lines 17-18.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu with Yu to obtain the invention as specified in claim 8.
Regarding claim 10, in which claim 7 is incorporated, Yu does not disclose wherein the evaluating the quality of the each of the contours is based on maximum concavity of the each of the contours exceeding a threshold.
Liu teaches wherein the evaluating the quality of the each of the contours is based on maximum concavity of the each of the contours exceeding a threshold (See Liu, Pg. 5, lines 26-27, then only keeping the concave point with the largest concave point value as the concave point of the concave part. Examiner considers the largest concave point as a threshold in which the maximum amount of concave points will be counted at).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the quality of the each of the contours is based on maximum concavity of the each of the contours exceeding a threshold based on the method of Liu’s reference. The suggestion/motivation would have been for the accuracy and speed of the outline dividing technology based on the concave point matching as suggested by Liu at Pg. 2, lines 17-18.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Liu with Yu to obtain the invention as specified in claim 10.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Diankov et al. (WO 2022/245842 A1, hereinafter, “Diankov”) and further in view of Ushijima (US 2013/0004019 A1, hereinafter, “Ushijima”).
Regarding claim 9, in which claim 7 is incorporated, Yu does not disclose wherein the evaluating the quality of the each of the contours is based on an average or median concavity of the each of the contours exceeding a threshold.
Ushijima teaches wherein the evaluating the quality of the each of the contours is based on an average or median concavity of the each of the contours exceeding a threshold (See Ushijima, ¶ [0045] the contour extraction unit 61 may determine the average of the pixel values in each region, and set, as a notable region, a region having the average closest to a reference value being preset in accordance with an assumed background. Examiner considers the reference value to act as a threshold value).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference wherein the evaluating the quality of the each of the contours is based on an average or median concavity of the each of the contours exceeding a threshold based on the method of Ushijima’s reference. The suggestion/motivation would have been to extracts, from an image containing a target region, a segment of a boundary of the target region which corresponds to a depressed portion as suggested by Ushijima at ¶ [0006].
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Ushijima with Yu to obtain the invention as specified in claim 9.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Yu et al. (US 10,614,340 B1, hereinafter, “Yu”) in view of Diankov et al. (WO 2022/245842 A1, hereinafter, “Diankov”), further in view of Yang et al. (An overview of edge and object contour detection, 2022, hereinafter, “Yang”), further in view of Liu et al. (CN 112270679 B, hereinafter, “Liu”), and further in view of Ushijima (US 2013/0004019 A1, hereinafter, “Ushijima”).
Regarding claim 13, in which claim 7 is incorporated, Yu does not disclose updating statistics for the object recognition process based on one or more of a number of the one or more objects having the quality exceeding a threshold, an average concavity of the one or more objects having the quality lower than the threshold, a median concavity of the one or more objects having the quality lower than the threshold, and a maximum concavity of the one or more objects having the quality lower than the threshold.
Yang teaches updating statistics for the object recognition process (See Yang, Pg 483. section 6.1, lines 1-3, Datasets are essential for edge and object contour detection in two aspects: (1) they are used as benchmarks for evaluating the quality of methods, and (2) they are used as training data for learning-based methods).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference to updating statistics for the object recognition process based on the method of Yang’s reference. The suggestion/motivation would have been to improve performances as suggested by Yang at Pg. 483, section 6.1, line 8.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
However, Yu and Yang do not teach [updating statistics for the object recognition process] based on one or more of a number of the one or more objects having the quality exceeding a threshold, an average concavity of the one or more objects having the quality lower than the threshold, a median concavity of the one or more objects having the quality lower than the threshold, and a maximum concavity of the one or more objects having the quality lower than the threshold.
Diankov teaches [updating statistics for the object recognition process] based on one or more of a number of the one or more objects having the quality exceeding a threshold (See Diankov, ¶ [00117] if the minimum viable region 3006 is comparable to the maximum candidate size 3018, there is a higher confidence that the minimum viable region 3006 accurately portrays the target object 3000 A), [an average concavity of the one or more objects] having the quality lower than the threshold (See Diankov, ¶ [00118] if the threshold is not surpassed, the certainty that the minimum viable region accurately represents the dimensions of the target object 3000A is lower),[ a median concavity of the one or more objects] having the quality lower than the threshold (See Diankov, ¶ [00118] if the threshold is not surpassed, the certainty that the minimum viable region accurately represents the dimensions of the target object 3000A is lower), [and a maximum concavity of the one or more objects] having the quality lower than the threshold (See Diankov, ¶ [00118] if the threshold is not surpassed, the certainty that the minimum viable region accurately represents the dimensions of the target object 3000A is lower).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference whering having the quality exceeding a threshold and having the quality lower than the threshold based on the method of Diankov’s reference. The suggestion/motivation would have been to increase the accuracy and efficiency of robotic object handling as suggested by Diankov in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
However, Yu, Yang, and Diankov do not teach an average concavity of the one or more objects, a median concavity of the one or more objects, and a maximum concavity of the one or more objects.
Ushijima teaches an average concavity of the one or more objects (See Ushijima, ¶ [0045] the contour extraction unit 61 may determine the average of the pixel values in each region) and a median concavity of the one or more objects (See Ushijima, ¶ [0045] the contour extraction unit 61 may determine the average of the pixel values in each region. Examiner considers there to be multiple pixels or concavities located. The user can choose to implement a type of calculation such as mean or median of the data set).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference to have an average concavity of the one or more objects and a median concavity of the one or more objects based on the method of Ushijima’s reference. The suggestion/motivation would have been to determine, based on a length of the first shortcut line or a length of a first route that extends along the contour line between the first and second contour points, whether or not a portion surrounded by the first shortcut line and the first route, not contained in the given region, is a depressed portion as suggested by Ushijima in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
However, Yu, Yang, Diankov, and Ushijima do not teach a maximum concavity of the one or more objects.
Liu teaches a maximum concavity of the one or more objects (See Liu, Pg. 4, lines 36-37, then only keeping the concave point with the maximum concave point value as the concave point of the concave part).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Yu’s reference a maximum concavity of the one or more objects based on the method of Liu’s reference. The suggestion/motivation would have been to find the matching point in the concave point sequence and the inner profile of the other concave edge as suggested by Liu in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Yang, Diankov, Ushijima, and Liu with Yu to obtain the invention as specified in claim 13.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhang (US 2022/0147732 A1) discloses an object recognition method and system to recognize objects from an image. Depth information is collected from the image followed by super pixel segmentation. A 3D image is generated and input into a neural network to then obtain a recognition result. The goal is to improve recognition accuracy and speed by providing training data go train a neural network.
Yano et al. (US 2020/0211221 A1) discloses an object recognition device and method consisting of a reference image with feature points. The sharpness or depth of the points in the image are calculated and a matching process then takes place. The different areas of the image are then extracted based on a grouping of different sharpness ranges. The aim is to improve the accuracy of object recognition even when there may be light or shadows introduced into an image.
Tan et al. (CN 101996414 B) discloses a method for rendering a concave polygon. Rendering is performed by first segmenting the polygon, analyzing pixels of the segmented convex polygons, and then using parameter information and coordinate information to build the complex shape. The goal is to reduce the time is takes to render these shapes and reduce cos with minimal calculations and accurate outputs.
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/JASMIN MARCELINO HERNAND/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
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