DETAILED ACTION
This communication is in response to the claims filed on 08/29/2024.
Application No: 18/811,992.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice of Pre-AIA or AIA Status
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 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.
Claim Objections
Claim 8 (and similarly claim 14 and claim 19) is objected to because of the following informalities: claim is not clarifying limitation, namely, “a predetermined value”. A value is a generic word and is not clearly defined in the claim. Appropriate correction is required.
Double Patenting Rejection (ODP)
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l) (1) - 706.02(l) (3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1,3,5 and 7-21 of the instant application (18/811,992) are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-3 of the U.S. Patent No. US 12046043 B2 (herein after ‘043 or reference patent), and claim 1, 3, 5 and 7-18 of copending Application No 18/811,957 (hear in after ‘957, reference application), This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Although the claims at issue are not identical, they are not patentably distinct from each other because all the claimed limitations are recited in the instant pending application are transparently found in the above reference patents with obvious wording variation. If pending claims are allowed, would improperly extend the "right to exclude" already granted in the reference patent(s).
Applicant is now attempting to claim broadly (or similarly) that which had been previously described in more details in the claims of the patent(s) with obvious wording variations. As an example, below is showing comparisons between claims of the pending instant application and claims of the reference patent(s) with wording variations.
The claim 1 in the instant application is as follows:
An information processing system comprising:
at least one memory storing instructions; and
at least one processor configured to execute the instructions to:
detect an object being placed and at least a part of a human from a video;
control to display a video frame of the video, the video frame including the object and the at least a part of a human,
wherein the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
The claim 1 in the reference patent ‘043 is as follows:
An information processing apparatus comprising: at least one memory storing instructions; and at least one processor configured to execute the instructions to:
detect a stationary object from a video frame; specify a first video frame including a target object detected as the stationary object; and display the first video frame and a second video frame that includes the target object and a person associated with the target object and is generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Analysis:
In the instant application, claim 1 discloses basic concept, including:
detect an object and a part of a human from a video,
display the video frame,
the video frame includes an image region, human being in the image region, the object and an around area of the object.
In the reference patent, claim 1 discloses basic concept, including:
detect a stationary object from a video frame,
display the first video frame, that includes the target object and a person associated with the target object,
second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Thus, the claim 1 of the reference patent discloses all limitations of the claim 1 of the instant application as shown by the underlines.
For the instant application: claim 1 is broader than the reference patent claim 1. Applicant has removed additional limitations such as, generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present, from the claim 1 of the reference patent, this makes claim 1 of the instant application broader.
Viewing underlined limitations, claim 1 of the instance application is generic to all that is recited in the claim 1 of the reference patent. Please note that, claim type in the reference patent may not be the same as that of the instant application claim type (i.e. a system, an apparatus, or a method), however steps used in any type of the reference patent claim are similar to the steps of the instant application claim, and producing equivalent concept results (i.e. claim type may be a system, apparatus, or method type; and transmitting or receiving messages directions may be opposite. Further It has been held that changing the language of the claim, thereby changing the scope of the claims slightly is an obvious expedient if the remaining elements perform the same function as before; therefore, omission of a reference element whose function is not needed would be obvious to one skilled in the art. Also see: In Re Goodman, 29 USPQ 2d 2010 CAFC 1993, states that a generic claim cannot be issued without a terminal disclaimer, if a species claim has been previously been claimed in a co-pending application).
Therefore, the instant application claim 1 is anticipated by the claim 1 of the reference patent as analyzed above; hence, claim 1 of the instant application is rejected under the Double Patenting doctrine.
The claim 3 in the instant application is as follows:
An information processing method executed by a computer, the information processing method comprising:
detecting an object being placed and at least a part of a human from a video;
controlling to display a video frame of the video, the video frame including the object and the at least a part of a human,
wherein the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
The claim 2 in the reference patent ‘043 is as follows:
An information processing method executed by a computer, the information processing method comprising:
detecting a stationary object from a video frame; specifying a first video frame including a target object detected as the stationary object; and displaying the first video frame and a second video frame that includes the target object and a person associated with the target object and is generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Analysis:
In the instant application, claim 3 discloses basic concept, including:
detect an object and a part of a human from a video,
display the video frame,
the video frame includes an image region, human being in the image region, the object and an around area of the object.
In the reference patent, claim 2 discloses basic concept, including:
detect a stationary object from a video frame,
display the first video frame, that includes the target object and a person associated with the target object,
second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Thus, the claim 2 of the reference patent discloses all limitations of the claim 3 of the instant application as shown by the underlines.
For the instant application: claim 3 is broader than the reference patent claim 2. Applicant has removed additional limitations such as, generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present, from the claim 2 of the reference patent, this makes claim 3 of the instant application broader.
Viewing underlined limitations, claim 3 of the instance application is generic to all that is recited in the claim 2 of the reference patent. Please note that, claim type in the reference patent may not be the same as that of the instant application claim type (i.e. a system, an apparatus, or a method), however steps used in any type of the reference patent claim are similar to the steps of the instant application claim, and producing equivalent concept results (i.e. claim type may be a system, apparatus, or method type; and transmitting or receiving messages directions may be opposite. Further It has been held that changing the language of the claim, thereby changing the scope of the claims slightly is an obvious expedient if the remaining elements perform the same function as before; therefore, omission of a reference element whose function is not needed would be obvious to one skilled in the art. Also see: In Re Goodman, 29 USPQ 2d 2010 CAFC 1993, states that a generic claim cannot be issued without a terminal disclaimer, if a species claim has been previously been claimed in a co-pending application).
Therefore, the instant application claim 3 is anticipated by the claim 2 of the reference patent as analyzed above; hence, claim 3 of the instant application is rejected under the Double Patenting doctrine.
The claim 5 in the instant application is as follows:
A non-transitory computer-readable medium storing a program for causing a computer to perform operations, the operations comprising:
detecting an object being placed and at least a part of a human from a video;
controlling to display a video frame of the video, the video frame including the object and the at least a part of a human,
wherein the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
The claim 3 in the reference patent ‘043 is as follows:
A non-transitory computer-readable medium storing a program for causing a computer to perform operations, the operations comprising:
detecting a stationary object from a video frame; specifying a first video frame including a target object detected as the stationary object; and displaying the first video frame and a second video frame that includes the target object and a person associated with the target object and is generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Analysis:
In the instant application, claim 5 discloses basic concept, including:
detect an object and a part of a human from a video,
display the video frame,
the video frame includes an image region, human being in the image region, the object and an around area of the object.
In the reference patent, claim 3 discloses basic concept, including:
detect a stationary object from a video frame,
display the first video frame, that includes the target object and a person associated with the target object,
second video frame indicates a state in which the person is present in a predetermined image area around the target object.
Thus, the claim 3 of the reference patent discloses all limitations of the claim 5 of the instant application as shown by the underlines.
For the instant application: claim 5 is broader than the reference patent claim 3. Applicant has removed additional limitations such as, generated chronologically before the first video frame, wherein the second video frame indicates a state in which the person is present, from the claim 3 of the reference patent, this makes claim 5 of the instant application broader.
Viewing underlined limitations, claim 5 of the instance application is generic to all that is recited in the claim 3 of the reference patent. Please note that, claim type in the reference patent may not be the same as that of the instant application claim type (i.e. a system, an apparatus, or a method), however steps used in any type of the reference patent claim are similar to the steps of the instant application claim, and producing equivalent concept results (i.e. claim type may be a system, apparatus, or method type; and transmitting or receiving messages directions may be opposite. Further It has been held that changing the language of the claim, thereby changing the scope of the claims slightly is an obvious expedient if the remaining elements perform the same function as before; therefore, omission of a reference element whose function is not needed would be obvious to one skilled in the art. Also see: In Re Goodman, 29 USPQ 2d 2010 CAFC 1993, states that a generic claim cannot be issued without a terminal disclaimer, if a species claim has been previously been claimed in a co-pending application).
Therefore, the instant application claim 5 is anticipated by the claim 3 of the reference patent as analyzed above; hence, claim 5 of the instant application is rejected under the Double Patenting doctrine.
The dependent claims of the instant application are as follows:
Claims 7-21.
The patent ‘043 dependent claims are as follows:
No dependent claims.
Analysis:
Further, analyzing and comparing dependent claims 7-21 of the instant application with independent claims 1-3 of the reference patent ‘043, it was found that they recite the similar limitation with wording changes.
Therefore, dependent claims 7-21 of the instant application are rejected under the anticipated type Double Patenting doctrine.
Note the issued claims of the reference patent ‘043 are narrower in scope such that the claimed limitations as recited in the instant (pending) application are encompassed by U.S. reference patent ‘043.
The claims 1, 3 and 5 in the instant application are summarized with common subject matter as follows:
detect an object being placed and at least a part of a human from a video;
control to display a video frame of the video, the video frame including the object and the at least a part of a human,
wherein the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
The claims 1, 3 and 5 in the reference application ‘957 are summarized with common subject matter as follows:
detect an arrived object from a video; specify a first video frame including a target object detected as the arrived object; control to display the first video frame; and display a second video frame including the target object and a person, the second video frame captured chronologically before the first video wherein the second video frame includes the person being present in a predetermined image area around the target object.
Analysis:
analyzing and comparing independent claims 1, 3 and 5 of the pending application with independent claims 1, 3 and 5 of the reference application ‘957, it was found that they recite the similar limitations with wording changes.
Therefore, the instant application independent claims 1, 3 and 5 are anticipated by the independent claims 1, 3 and 5 of the reference application ‘957 as analyzed above; hence, claims 1, 3 and 5 of the instant application are rejected under the Double Patenting doctrine.
Further, analyzing and comparing dependent claims 7-21 of the pending application with dependent claims 7-18 of the reference application ‘957, it was found that they recite the similar limitations with wording changes.
Therefore, the instant application dependent claims 7-21 are anticipated by the dependent claims 7-18 of the reference application ‘957 as analyzed above; hence, claim s 7-21 of the instant application are rejected under the Double Patenting doctrine.
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U. S. 1, 148 USPQ 459 (1966), that are applied 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 nonobviousness.
Claims 1, 3, 5, 8-9, 13-14, 18 and 19 are rejected under 35 U. S. C. 103 as being unpatentable over Oami et al. (US 20150248587 A1) in view of TAKEDA et al. (US 20180150955 A1).
Regarding claim 1, Oami teaches an information processing system ([0007], Fig. 1, Fig. 8, e.g. An image processing method (i.e. a method steps executed in a system) according to the present invention comprises the steps of: accepting input of videos captured by a plurality of video cameras; predicting a video camera on which an object detected in the inputted videos is to appear next; and announcing a confusability of the object according to a similarity between the detected object and another object that is likely to appear in a video of the predicted video camera and causing a display device to display a video from the predicted video camera. [0024] While the surveillance system 1 will be described hereinafter as a system for conducting surveillance on a person image-captured by the video camera 200, surveillance subjects are not limited thereto. For example, the surveillance subjects may be a moving object (an object or a mobile object) such as a vehicle or a motorcycle), comprising:
at least one memory storing instructions; and
at least one processor ([0086], e.g. The memory 803 is a storage medium such as a random access memory (RAM). The memory 803 temporarily stores program codes of the program that is executed by the processor 801 and data necessary when executing the program. For example, a stack region that is required when executing the program is secured in a storage region of the memory 803), configured to execute the instructions to:
detect an object being placed ([0007], e.g. predicting a video camera on which an object detected in the inputted videos is to appear next. [0024] For example, the surveillance subjects may be a moving object (an object or a mobile object) such as a vehicle or a motorcycle.), and
at least a part of a human from a video ([0063], e.g. The object detecting/tracking unit 610 uses the object detecting unit 611 to detect a person as an object from a video acquired by each of the image acquiring units 601. [0064] Furthermore, by comparing images (frames) in a time series, the object tracking unit 613 tracks each person extracted as an object in a same angle of view (i.e. extracted a part of a human from a video), and generates object tracking information);
control to display a video frame of the video, the video frame including the object and the at least a part of a human ([0047], e.g. FIG. 5 is a diagram showing a specific example when a person has appeared on the video image in the video display region 30. In the example shown in FIG. 5, the image 31 indicating that the appeared person is highly likely to be the person who is the surveillance subject and the image 32 indicating that the appeared person is highly likely to be a different person (i.e. a moving or a stationary object that is not human) who may be confused with the person who is the surveillance subject are arranged around the appeared person. [0049] Moreover, a method of alerting the user, shapes of the images 31 and 32, and the like are not limited to those described above. For example, a location where the surveillance subject is likely to appear may be opaquely painted out and, when issuing an alert, a display method such as changing the color of the image 31 or causing the image 31 to blink (instead of displaying the image 32) can be used (i.e. controlling displaying video frames and images)).
Oami teaches an image processing system, capable of suppressing errors related to association of a person appearing in a video. However, Oami differs from the claimed invention in not specifically and clearly describing wherein
the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
However, in the analogous field of endeavor, TAKEDA teaches wherein
the video frame includes an image region, at least the part of the human being in the image region ([0043], e.g. With reference to FIG. 3, there is shown an input image frame 302 of a video captured by the image-capture device 104. The input image frame 302 may include a human object 304A, an inanimate object 304B, and a background (BG) region 306 (i.e. part of the human being in the image region)),
the image region including the object and an around area of the object ([0027], e.g. The image-processing device 102 may be further configured to detect one or more FG regions to be removed from the segregated FG region based on a face detection and/or a human body detection technique (i.e. an around area of the object). For example, FG regions that correspond to objects other than human may be removed. The first FG mask may be selected from one or more other FG masks for further processing and FG mask correction. The selection of the first FG mask from the one or more FG masks of the FG region may be executed based on detection of face, human body, gesture, motion, shape, and/or edge (i.e. mage region including the object and an around area of the object)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of TAKEDA within the method of Oami. The motivation to combine references is that the combined method provides improved techniques for video segmentations. The image segmentation, which may refer to the partitioning of an image into several regions based on certain rules. Although various segmentation methods have been known to separate foreground objects from the background of an image or a video, the complexity, accuracy, and computational resource requirements vary based on the objective to be achieved. The present embodiment provides a capability to the image-processing device to accurately segment a desired object, such as the human object, from the background by itself (See TAKEDA [0004, 0081]).
Regarding claim 3, Oami teaches an information processing method executed by a computer ([0007], Fig. 1, Fig. 8, e.g. An image processing method according to the present invention comprises the steps of: accepting input of videos captured by a plurality of video cameras; predicting a video camera on which an object detected in the inputted videos is to appear next; and announcing a confusability of the object according to a similarity between the detected object and another object that is likely to appear in a video of the predicted video camera and causing a display device to display a video from the predicted video camera. [0024] While the surveillance system 1 will be described hereinafter as a system for conducting surveillance on a person image-captured by the video camera 200, surveillance subjects are not limited thereto. For example, the surveillance subjects may be a moving object (an object or a mobile object) such as a vehicle or a motorcycle), the information processing method comprising:
detecting an object being placed [0007], e.g. predicting a video camera on which an object detected in the inputted videos is to appear next. [0024] For example, the surveillance subjects may be a moving object (an object or a mobile object) such as a vehicle or a motorcycle.), and
at least a part of a human from a video ([0063], e.g. The object detecting/tracking unit 610 uses the object detecting unit 611 to detect a person as an object from a video acquired by each of the image acquiring units 601. [0064] Furthermore, by comparing images (frames) in a time series, the object tracking unit 613 tracks each person extracted as an object in a same angle of view (i.e. extracted a part of a human from a video), and generates object tracking information);
controlling to display a video frame of the video, the video frame including the object and the at least a part of a human ([0047], e.g. FIG. 5 is a diagram showing a specific example when a person has appeared on the video image in the video display region 30. In the example shown in FIG. 5, the image 31 indicating that the appeared person is highly likely to be the person who is the surveillance subject and the image 32 indicating that the appeared person is highly likely to be a different person (i.e. a moving or a stationary object that is not human) who may be confused with the person who is the surveillance subject are arranged around the appeared person. [0049] Moreover, a method of alerting the user, shapes of the images 31 and 32, and the like are not limited to those described above. For example, a location where the surveillance subject is likely to appear may be opaquely painted out and, when issuing an alert, a display method such as changing the color of the image 31 or causing the image 31 to blink (instead of displaying the image 32) can be used (i.e. controlling displaying video frames and images)).
Oami teaches an image processing system, capable of suppressing errors related to association of a person appearing in a video. However, Oami differs from the claimed invention in not specifically and clearly describing wherein
the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
However, in the analogous field of endeavor, TAKEDA teaches wherein
the video frame includes an image region, at least the part of the human being in the image region ([0043], e.g. With reference to FIG. 3, there is shown an input image frame 302 of a video captured by the image-capture device 104. The input image frame 302 may include a human object 304A, an inanimate object 304B, and a background (BG) region 306 (i.e. part of the human being in the image region)),
the image region including the object and an around area of the object ([0027], e.g. The image-processing device 102 may be further configured to detect one or more FG regions to be removed from the segregated FG region based on a face detection and/or a human body detection technique (i.e. an around area of the object). For example, FG regions that correspond to objects other than human may be removed. The first FG mask may be selected from one or more other FG masks for further processing and FG mask correction. The selection of the first FG mask from the one or more FG masks of the FG region may be executed based on detection of face, human body, gesture, motion, shape, and/or edge (i.e. mage region including the object and an around area of the object)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of TAKEDA within the method of Oami. The motivation to combine references is that the combined method provides improved techniques for video segmentations. The image segmentation, which may refer to the partitioning of an image into several regions based on certain rules. Although various segmentation methods have been known to separate foreground objects from the background of an image or a video, the complexity, accuracy, and computational resource requirements vary based on the objective to be achieved. The present embodiment provides a capability to the image-processing device to accurately segment a desired object, such as the human object, from the background by itself (See TAKEDA [0004, 0081]).
Regarding claim 5, Oami teaches a non-transitory computer-readable medium storing a program for causing a computer to perform operations ([0086], e.g. The memory 803 is a storage medium such as a random access memory (RAM, i.e. a non-transitory computer readable medium)). The memory 803 temporarily stores program codes of the program that is executed by the processor 801 and data necessary when executing the program. For example, a stack region that is required when executing the program is secured in a storage region of the memory 803), the operations comprising:
detecting an object being placed ([0007], e.g. predicting a video camera on which an object detected in the inputted videos is to appear next. [0024] For example, the surveillance subjects may be a moving object (an object or a mobile object) such as a vehicle or a motorcycle.), and
at least a part of a human from a video ([0063], e.g. The object detecting/tracking unit 610 uses the object detecting unit 611 to detect a person as an object from a video acquired by each of the image acquiring units 601. [0064] Furthermore, by comparing images (frames) in a time series, the object tracking unit 613 tracks each person extracted as an object in a same angle of view (i.e. extracted a part of a human from a video), and generates object tracking information);
controlling to display a video frame of the video, the video frame including the object and the at least a part of a human control to display a video frame of the video, the video frame including the object and the at least a part of a human ([0047], e.g. FIG. 5 is a diagram showing a specific example when a person has appeared on the video image in the video display region 30. In the example shown in FIG. 5, the image 31 indicating that the appeared person is highly likely to be the person who is the surveillance subject and the image 32 indicating that the appeared person is highly likely to be a different person (i.e. a moving or a stationary object that is not human) who may be confused with the person who is the surveillance subject are arranged around the appeared person. [0049] Moreover, a method of alerting the user, shapes of the images 31 and 32, and the like are not limited to those described above. For example, a location where the surveillance subject is likely to appear may be opaquely painted out and, when issuing an alert, a display method such as changing the color of the image 31 or causing the image 31 to blink (instead of displaying the image 32) can be used (i.e. controlling displaying video frames and images)).
Oami teaches an image processing system, capable of suppressing errors related to association of a person appearing in a video. However, Oami differs from the claimed invention in not specifically and clearly describing wherein
the video frame includes an image region, at least the part of the human being in the image region, the image region including the object and an around area of the object.
However, in the analogous field of endeavor, TAKEDA teaches wherein
the video frame includes an image region, at least the part of the human being in the image region ([0043], e.g. With reference to FIG. 3, there is shown an input image frame 302 of a video captured by the image-capture device 104. The input image frame 302 may include a human object 304A, an inanimate object 304B, and a background (BG) region 306 (i.e. part of the human being in the image region),
the image region including the object and an around area of the object ([0027], e.g. The image-processing device 102 may be further configured to detect one or more FG regions to be removed from the segregated FG region based on a face detection and/or a human body detection technique (i.e. an around area of the object). For example, FG regions that correspond to objects other than human may be removed. The first FG mask may be selected from one or more other FG masks for further processing and FG mask correction. The selection of the first FG mask from the one or more FG masks of the FG region may be executed based on detection of face, human body, gesture, motion, shape, and/or edge (i.e. mage region including the object and an around area of the object)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of TAKEDA within the method of Oami. The motivation to combine references is that the combined method provides improved techniques for video segmentations. The image segmentation, which may refer to the partitioning of an image into several regions based on certain rules. Although various segmentation methods have been known to separate foreground objects from the background of an image or a video, the complexity, accuracy, and computational resource requirements vary based on the objective to be achieved. The present embodiment provides a capability to the image-processing device to accurately segment a desired object, such as the human object, from the background by itself (See TAKEDA [0004, 0081]).
Regarding claim 8, Oami in view of TAKEDA teaches all the limitations of claim 1. Oami further teaches wherein the object is detected as being placed and stationary ([0045], Fig. 5, e.g. an image 32 (i.e. a stationery object) that alerts the user is arranged in a vicinity of the image 31 showing that the person who is the surveillance subject is highly likely to appear).
Regarding claim 9, Oami in view of TAKEDA teaches all the limitations of claim 1. TAKEDA further teaches wherein the object is detected as stationary in a case where a variation amount of the object is equal to or less than a predetermined value ([0023], e.g. The sequence of image frames 112 refer to a video of a scene as viewed and captured by the user 110, by the image-capture device 104. The sequence of image frames 112 may include one or more objects, such as the object 114. In accordance with an embodiment, the object 114 may be an object-of-interest to be segmented from the sequence of image frames 112 (i.e. segmented based on variation amount of the object comprising a predetermined value). Examples of the object 114 may include, but are not limited to a human object, an animal, or a non-human or inanimate object, such as a vehicle or a sports item).
The motivation to combine references of TAKEDA within the method of Oami before the effective filing date of the invention is that the combined method provides improve techniques for an image-processing device and method for foreground mask correction for object segmentation, includes receipt of a sequence of image frames. A first FG mask is estimated using depth information associated with the input image frame and by binarizing a difference between the input image frame and a background (BG) image of the input image frame (See TAKEDA ([abstract]).
Regarding claim 13, Oami in view of TAKEDA teaches all the limitations of claim 3. Oami further teaches wherein the object is detected as being placed and stationary ([0045], Fig. 5, e.g. an image 32 (i.e. a stationery object) that alerts the user is arranged in a vicinity of the image 31 showing that the person who is the surveillance subject is highly likely to appear).
Regarding claim 14, Oami in view of TAKEDA teaches all the limitations of claim 3. TAKEDA further teaches wherein the object is detected as stationary in a case where a variation amount of the object is equal to or less than a predetermined value ([0023], e.g. The sequence of image frames 112 refer to a video of a scene as viewed and captured by the user 110, by the image-capture device 104. The sequence of image frames 112 may include one or more objects, such as the object 114. In accordance with an embodiment, the object 114 may be an object-of-interest to be segmented from the sequence of image frames 112 (i.e. segmented based on variation amount of the object comprising a predetermined value). Examples of the object 114 may include, but are not limited to a human object, an animal, or a non-human or inanimate object, such as a vehicle or a sports item).
The motivation to combine references of TAKEDA within the method of Oami before the effective filing date of the invention is that the combined method provides improve techniques for an image-processing device and method for foreground mask correction for object segmentation, includes receipt of a sequence of image frames. A first FG mask is estimated using depth information associated with the input image frame and by binarizing a difference between the input image frame and a background (BG) image of the input image frame (See TAKEDA ([abstract]).
Regarding claim 18, Oami in view of TAKEDA teaches all the limitations of claim 5. Oami further teaches wherein the object is detected as being placed and stationary ([0045], Fig. 5, e.g. an image 32 (i.e. a stationery object) that alerts the user is arranged in a vicinity of the image 31 showing that the person who is the surveillance subject is highly likely to appear).
Regarding claim 19, Oami in view of TAKEDA teaches all the limitations of claim 5. TAKEDA further teaches wherein the object is detected as stationary in a case where a variation amount of the object is equal to or less than a predetermined value ([0023], e.g. The sequence of image frames 112 refer to a video of a scene as viewed and captured by the user 110, by the image-capture device 104. The sequence of image frames 112 may include one or more objects, such as the object 114. In accordance with an embodiment, the object 114 may be an object-of-interest to be segmented from the sequence of image frames 112 (i.e. segmented based on variation amount of the object comprising a predetermined value). Examples of the object 114 may include, but are not limited to a human object, an animal, or a non-human or inanimate object, such as a vehicle or a sports item).
The motivation to combine references of TAKEDA within the method of Oami before the effective filing date of the invention is that the combined method provides improve techniques for an image-processing device and method for foreground mask correction for object segmentation, includes receipt of a sequence of image frames. A first FG mask is estimated using depth information associated with the input image frame and by binarizing a difference between the input image frame and a background (BG) image of the input image frame (See TAKEDA ([abstract]).
Allowable Subject Matter
Claims 7, 10-12, 15-17, 20 and 21 are objected to as being dependent upon a rejected base claim, but would be allowable, if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and amending claims to overcome any objection(s) and /or rejection(s) set forth in this Office action.
Prior Art Record
The prior art made of record and not relied upon is considered pertinent
to applicant’s disclosure.
Buehler, Christopher J. (US-20040119848-A1) - Method and apparatus for computerized image background analysis.
KANG; Ji-hong (US-20150092982-A1) - IMAGE PROCESSING APPARATUS AND CONTROL METHOD THEREOF.
Adachi; Keiji (US-20150215546-A1) - CONTROL APPARATUS, CONTROL METHOD, AND STORAGE MEDIUM.
GOLDNER; Vladimir (US-20160283798-A1) - SYSTEM AND METHOD FOR AUTOMATIC CALCULATION OF SCENE GEOMETRY IN CROWDED VIDEO SCENES.
TAKAHASHI; Kosuke ( US-20190022492-A1) - VIRTUAL ENVIRONMENT CONSTRUCTION APPARATUS, METHOD, AND COMPUTER READABLE MEDIUM.
ISHIKAWA, MASUMI (WO-2012153747-A1) - INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND INFORMATION PROCESSING PROGRAM.
Conclusion
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/MAHENDRA R PATEL/ Primary Examiner, Art Unit 2645
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