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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/10/2026 has been entered.
Response to Arguments
Applicant's arguments filed 04/03/2026 have been fully considered.
Regarding to claim objections of claim 11, the amendment has cured the basis of claim objections. Therefore, the claim objections of claim 11 is hereby withdrawn.
Regarding to claims 10, and 15-17, the amendment has cured the basis of 35 U.S.C. 112(b). Therefore, the 35 U.S.C. 112(b) rejection of claims 10, and 15-17 is hereby withdrawn.
Regarding to 35 U.S.C 112 (f) interpretation, the applicant acknowledges the 35 U.S.C 112 (f) interpretation. The amendment does not overcome the 112 (f) interpretation. The specification does not overcome the 35 U.S.C 112 (f) interpretation. Therefore, the examiner maintains the 35 U.S.C 112 (f) interpretation.
Regarding to claim 1, the applicant argues that cited arts fail to teach or suggest “taking a first real-time image position of the first target as a center, drawing a geometric shape with a preset size around the first target such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image” recited in claim 1. The arguments have been fully considered. The argument according “such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image” is persuasive. Therefore, the 35 U.S.C 103 rejection has been withdrawn. However, upon further consideration, new grounds of rejection are made in newly applied art. The argument according “taking a first real-time image position of the first target as a center, drawing a geometric shape with a preset size around the first target” is not persuasive. The examiner cannot concur with the applicant for following reasons:
Teng Long discloses “taking a first real-time image position of the first target as a center, drawing a geometric shape with a preset size around the first target”. For example, in paragraph [0064], Teng Long teaches the objects in the image are labeled by obtaining the outline of the objects through image processing technology, such as edge detection algorithms, and labeling the objects by using geometric shapes to surround the outline of the objects; Teng Long further teaches the objects are inside of the outline; Teng Long further more teaches drawing geometric shapes to surround the outline of the objects. In paragraph [0066], Teng Long teaches using rectangles, i.e. fixed size geometric shape, of different colors to mark different objects in the image. In paragraph [0076], Teng Long teaches the assisted driving device 200 sends the target object's location information to the UAV 100. In paragraph [0077], Teng Long teaches displaying an image screen including the target object, and labeling the object in the image screen. In paragraph [0085], Teng Long teaches annotating the object in the image screen.
Claims 8 and 15 are not allowable due to the similar reasons as discussed above.
The dependent claims of claims 1, 8, and 15 are not allowable due to the similar reasons as discussed above.
35 USC § 112 (f) Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: a data acquisition module, a target labeling module , and an image display module in claims 8-9.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Specification
The disclosure is objected to because of the following informalities: the paragraphs of the specification are not numbered. Please number the paragraphs of the specification. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 8, and 15 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The specification describes “by taking a first image position of a target as a center, a geometric shape with a preset size is drawn, or a preset picture is pasted to the first image position” in page 5. The specification further describes “determining positioning information of the at least one target in an actual environment according to the first image coordinates of the at least one target “ in page 5. “However, the specification does not describe “the center of the geometric shape” and “the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image”. Therefore, the language “the center of the geometric shape” and “the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image” are new matter.
Claims 2-7, 9-14, and 16-17 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph due to dependency of claim 1, 8, and 15.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 1 recites the limitation “the center of the geometric shape” in lines 10-11. There is insufficient antecedent basis for this limitation in the claim.
Claims 8 and 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite due to the similar reasons as discussed above.
Claims 2-7, 9-14, and 16-17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite due to dependence of claim 1, 8, and 15.
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.
Claims 1-17 are rejected under 35 U.S.C. 103 as being unpatentable over Teng Long (CN106339691A; English Translation by Machine) in view of Yang (US 20220237908 A1), and further in view of Bar-Nahum (US 20190025858 A1).
Regarding to claim 1 (Currently Amended), Teng Long discloses a target labeling method ([0001]: a method and apparatus for labeling objects; [0011]: provide a method for labeling objects; [0033]: the device for labeling objects; [0038]: UAV; the drone 100 communicates with the driver assistance device 200 via the network 300; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky), wherein the method comprises:
acquiring a first real-time image sent by an unmanned aerial vehicle and first target information of at least one target identified in the first real-time image ([0012]: the drone acquires panoramic images and sends the panoramic images to the driver assistance device; [0017]: the driver assistance system receives panoramic images acquired by the drone; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky; [0063]: receive the location of the target object from the assisted driving device 200; [0076]: send the target object's location information to the UAV 100), the first target information comprising first image coordinates of the target in the first real-time image ([0063]: receive the location of the target object from the assisted driving device 200; [0076]: send the target object's location information to the UAV 100; [0078]: the driver assistance device 200 uses rectangles of different colors to mark different objects in the image; the names of the objects and their distances from the drone are displayed at the marked locations of different objects; [0084]: the location information of the target object is sent to the UAV 100);
processing the at least one target at a corresponding position in the first real-time image according to the first target information of the at least one target so as to label the at least one target ([0018]: the driver assistance device performs visual scene analysis on the panoramic image to obtain the scene and objects in the panoramic image; [0019]: the driver assistance system performs target recognition on objects in the scene corresponding to the panoramic image; [0020]: display an image containing the target object; the object in the image is labeled; [0061]: the assisted driving device 200 marks the target object in the image screen);
taking a first real-time image position of the first target as a center, drawing a geometric shape with a preset size around the first target ([0064]: the objects in the image are labeled by obtaining the outline of the objects through image processing technology, such as edge detection algorithms, and labeling the objects by using geometric shapes to surround the outline of the objects; the objects are inside of the outline; draw geometric shapes to surround the outline of the objects; label the objects by using geometric shapes to surround the outline of the objects; Teng Long teaches the objects are inside of the outline; Teng Long further teaches drawing geometric shapes with preset size to surround the outline of the object; [0066]: use rectangles, i.e. fixed size geometric shape, of different colors to mark different objects in the image; [0076]: the assisted driving device 200 sends the target object's location information to the UAV 100; [0077]: display an image screen including the target object and label the object in the image screen; [0085]: annotate the object in the image screen); and
displaying the processed first real-time image ([0015]: the driver assistance device displays an image including the target object and labels the object in the image; [0020]: an image containing the target object is displayed, and the object in the image is labeled; [0061]: the assisted driving device 200 displays an image screen including the target object and marks the object in the image screen; [0085]: display an image screen including the target object when the target object exists, and to annotate the object in the image screen).
Teng Long fails to explicitly disclose:
rendering and rendered;
such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image.
In same field of endeavor, Yang teaches:
rendering and rendered ([0028]: an object previously rendered; [0030]: the objects in the computer rendered scene; [0052]: render multiple objects; [0059]: a computer rendered object).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Teng Long to include rendering and rendered as taught by Yang. The motivation for doing so would have been to improve robust detection and classification; render multiple objects; to calculate a distance of the camera from a computer rendered object; improve the detection of real-world object as taught by Yang in paragraphs [0052], [0059], and [0062].
Teng Long in view of Yang fails to explicitly disclose:
such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image.
In same field of endeavor, Bar-Nahum teaches:
such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image ([0049]: label one or more objects; [0060]: label objects as a UAV; label objects as a bird; label objects as a plane; [0094]: a bounding box outlines an area within the image that includes the image portion with the target; bounding box outlines the minimum sized box, i.e. fixed preset size, that includes detected features of the target; the shapes of UAV, bird, and plane are not square; Fig. 6; [0102]: Graph representation 600 shows target 602, an x-axis 604, y-axis 606, 2D vector 608, degX 610, and degY 612; target 602 is positioned at the center of square bounding box;
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; y-axis 606, 2D vector 608, degX 610, and degY 612 are independent of the actual size of target 602; the shapes of UAV, bird, and plane are not square).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Teng Long in view of Yang to include such that the first target is positioned at the center of the geometric shape and the geometric shape has a fixed preset size that is independent of the actual size of the first target in the first real-time image as taught by Bar-Nahum. The motivation for doing so would have been to label one or more objects; to train a machine learning model to label an object; to outline an area within the image that includes the image portion with the target as taught by Bar-Nahum in paragraphs [0049], [0060], and [0094].
Regarding to claim 2 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 1, wherein the step of rendering the at least one target at a corresponding position in the first real-time image according to the first target information of the at least one target so as to label the at least one target (same as rejected in claim 1) comprises:
processing and displaying a contour of the at least one target and/or a type of the at least one target in a preset first labeling manner at a corresponding position in the first real-time image according to the first target information of the at least one target (Teng Long; [0061]: the assisted driving device 200 displays an image screen including the target object and marks the object in the image screen; [0064]: the objects in the image are labeled by obtaining the outline of the objects through image processing technology and labeling the objects by using geometric shapes to surround the outline of the objects; [0065]: the assisted driving device 200 displays the name of the object and the distance).
Teng Long in view of Yang and Bar-Nahum further disclose rendering (Yang; [0028]: an object previously rendered; [0030]: the objects in the computer rendered scene; [0052]: render multiple objects; [0059]: a computer rendered object).
Same motivation of claim 1 is applied here.
Regarding to claim 3 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 1, wherein the method further comprises:
determining positioning information of the at least one target in an actual environment according to the first image coordinates of the at least one target (Teng Long; [0056]: identify objects in the scene; [0057]: the assisted driving device 200 performs target recognition on objects in the scene corresponding to the panoramic image; [0063]: receive the location of the target object from the assisted driving device 200; [0076]: send the target object's location information to the UAV 100; [0078]: the driver assistance device 200 uses rectangles of different colors to mark different objects in the image; the names of the objects and their distances from the drone are displayed at the marked locations of different objects; [0084]: the location information of the target object is sent to the UAV 100);
matching the positioning information with position information of each target in a preset model library to acquire additional information of the at least one target (Teng Long; [0060]: the objects in the scene corresponding to the panoramic image are compared with the target objects pre-stored in the database to identify the target objects; a successful match indicates the existence of the target object; [0075]); and
rendering the at least one target at a corresponding position in the first real-time image according to the first target information of the at least one target and the additional information of the at least one target so as to label the first target information and the additional information of the at least one target (Teng Long; [0061]: the assisted driving device 200 displays an image screen including the target object and marks the object in the image screen; [0064]: the objects in the image are labeled by obtaining the outline of the objects through image processing technology and labeling the objects by using geometric shapes to surround the outline of the objects; [0065]: the assisted driving device 200 displays the name of the object and the distance, i.e. additional information).
Teng Long in view of Yang and Bar-Nahum further disclose rendering (Yang; [0028]: an object previously rendered; [0030]: the objects in the computer rendered scene; [0052]: render multiple objects; [0059]: a computer rendered object).
Same motivation of claim 1 is applied here.
Regarding to claim 4 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 1, wherein the method further comprises:
sending a target labeling request to the unmanned aerial vehicle, the target labeling request carrying identification information of a target (Teng Long; [0063]: UAV receives the location of the target object from the assisted driving device 200; [0076]: send the target object's location information to the UAV 100; [0084]: the location information of the target object is sent to the UAV 100); and
acquiring the first real-time image sent by the unmanned aerial vehicle and the first target information of the at least one target identified based on the identification information in the first real-time image (Teng Long; [0012]: the drone acquires panoramic images and sends the panoramic images to the driver assistance device; [0017]: the driver assistance system receives panoramic images acquired by the drone; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky; [0056]: identify objects in the scene; [0057]: the assisted driving device 200 performs target recognition on objects in the scene corresponding to the panoramic image).
Regarding to claim 5 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 4, wherein the method further comprises:
sending a target tracking request to the unmanned aerial vehicle, the target tracking request carrying first image coordinates of a tracked target in the first real-time image (Teng Long; [0026]: use panoramic optical image recognition technology to acquire panoramic images; the assisted driving device performs scene analysis and object target recognition on the image, determines the target object, tracks and identifies the identified target object, and records the detection distance result; [0063]: after receiving the location of the target object from the assisted driving device 200, the UAV 100 adjusts the gimbal);
acquiring a second real-time image sent by the unmanned aerial vehicle and second target information of the tracked target identified in the second real-time image, the second target information comprising second image coordinates of the tracked target in the second real-time image (Teng Long; [0026]: use panoramic optical image recognition technology to acquire panoramic images; the assisted driving device performs scene analysis and object target recognition on the image, determines the target object, tracks and identifies the identified target object, and records the detection distance result; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky; [0056]: identify objects in the scene; [0057]: the assisted driving device 200 performs target recognition on objects in the scene corresponding to the panoramic image; [0063]: after receiving the location of the target object from the assisted driving device 200, the UAV 100 adjusts the gimbal so that the millimeter continuous wave radar is aimed at the location of the target object; [0076]: if a target object is located, the assisted driving device 200 sends the target object's location information to the UAV 100 using a millimeter continuous wave radar);
processing the tracked target in a preset second labeling manner at a corresponding position in the second real-time image according to the second target information so as to label the tracked target (Teng Long; [0018]: the driver assistance device performs visual scene analysis on the panoramic image to obtain the scene and objects in the panoramic image; [0019]: the driver assistance system performs target recognition on objects in the scene corresponding to the panoramic image; [0020]: an image containing the target object is displayed, and the object in the image is labeled; [0061]: the assisted driving device 200 displays an image screen including the target object and marks the object in the image screen); and
displaying the processed second real-time image (Teng Long; [0015]: the driver assistance device displays an image including the target object and labels the object in the image; [0020]: an image containing the target object is displayed, and the object in the image is labeled; [0061]: the assisted driving device 200 displays an image screen including the target object and marks the object in the image screen; [0085]: display an image screen including the target object when the target object exists, and to annotate the object in the image screen).
Teng Long in view of Yang and Bar-Nahum further discloses:
rendering and rendered ([0028]: an object previously rendered; [0030]: the objects in the computer rendered scene; [0052]: render multiple objects; [0059]: a computer rendered object).
Same motivation of claim 1 is applied here.
Regarding to claim 6 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 5, wherein the method further comprises:
acquiring historical image coordinates of the tracked target in the second real-time image before current time (Teng Long; [0060]: the objects in the scene corresponding to the panoramic image are compared with the target objects pre-stored in the database, i.e. historical image, to identify the target objects; [0075]);
Teng Long in view of Yang and Bar-Nahum further discloses:
acquiring historical image coordinates of the tracked target in the second real-time image before current time (Yang; Fig. 1; [0028]: by changing the time of day, the moving ground object is viewed differently under different settings; [0029]: the data is image data or video data of computer rendered terrain and objects and stored in a memory for future use in a synthetic scene; Fig. 5; [0041]: classify the object as an object that moves through and/or is found in the air; [0059]: the generated image data from the in-flight camera is stored in a memory; [0076]: the electronic device 1100 generates models learned from the stored dataset, i.e., historical image; [0171]: compare the real-world, target object to stored objects in the database, i.e. historical image); and
rendering a moving track of the tracked target in the second real-time image according to the historical image coordinates and the second image coordinates of the tracked target (Yang; Fig. 1; [0028]: one or more elements 112 are independently changed for a particular scene; by changing the time of day, the moving ground object is viewed differently under different settings; the synthetic scene includes a clear sky in the morning in an urban location and include a car and a person on the sidewalk as objects; [0029]: video data of computer rendered terrain and objects; Fig. 5; [0041]: classify the object as an object that moves through and/or is found in the air; [0062]: video data of particular areas of the scene).
Same motivation of claim 1 is applied here.
Regarding to claim 7 (Original), Teng Long in view of Yang and Bar-Nahum discloses the method according to claim 5, wherein the method further comprises:
acquiring target loss information of the tracked target sent by the unmanned aerial vehicle (Teng Long; [0060]: the objects in the scene corresponding to the panoramic image are compared with the target objects pre-stored in the database to identify the target objects; a successful match indicates the existence of the target object; otherwise, it does not exist; [0075]: if the comparison is successful, it indicates that the target object exists; otherwise, it does not exist); and
rendering relevant information indicating that the tracked target is lost in the second real-time image according to the target loss information (Teng Long; [0075]: if the comparison is successful, it indicates that the target object exists; otherwise, it does not exist; [0077]: when a target object exists, display an image screen including the target object and label the object in the image screen; [0085]: display an image screen including the target object when the target object exists, and to annotate the object in the image screen).
Regarding to claim 8 (Currently Amended), Teng Long discloses a target labeling apparatus ([0001]: a method and apparatus for labeling objects; [0011]: provide a method for labeling objects; [0033]: the device for labeling objects; [0038]: UAV; the drone 100 communicates with the driver assistance device 200 via the network 300; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky), comprising:
a data acquisition module, configured to ([0080]: a receiving module[ [0086]: a panoramic optical camera);
a target labeling module, configured to([0043]: the object labeling device 220; [0080]: a visual scene analysis module 2202, and a target recognition module 2203); and
an image display module, configured to ([0080]: a display module; [0085]: display an image screen).
The rest claim limitations are similar to claim limitations recited in claim 1. Therefore, same rational used to reject claim 1 is also used to reject claim 8.
Regarding to claim 9 (Original), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 8, the target labeling module is further configured to:
The rest claim limitations are similar to claim limitations recited in claim 2. Therefore, same rational used to reject claim 2 is also used to reject claim 9.
Regarding to claim 10 (Currently Amended), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 8, wherein the target labeling module is further configured to:
the rest claim limitations are similar to claim limitations recited in claim 3. Therefore, same rational used to reject claim 3 is also used to reject claim 10.
Regarding to claim 11 (Currently Amended), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 8, wherein the target labeling apparatus is further configured to:
the rest claim limitations are similar to claim limitations recited in claim 4. Therefore, same rational used to reject claim 4 is also used to reject claim 11.
Regarding to claim 12 (Original), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 11, wherein the target labeling apparatus is further configured to:
the rest claim limitations are similar to claim limitations recited in claim 5. Therefore, same rational used to reject claim 5 is also used to reject claim 12.
Regarding to claim 13 (Original), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 12, wherein the target labeling apparatus is further configured to:
the rest claim limitations are similar to claim limitations recited in claim 6. Therefore, same rational used to reject claim 6 is also used to reject claim 13.
Regarding to claim 14 (Original), Teng Long in view of Yang and Bar-Nahum discloses the target labeling apparatus according to claim 12, wherein the target labeling apparatus is further configured to:
the rest claim limitations are similar to claim limitations recited in claim 7. Therefore, same rational used to reject claim 7 is also used to reject claim 14.
Regarding to claim 15 (Currently Amended), Teng Long discloses an electronic device ([0001]: a method and apparatus for labeling objects; [0011]: provide a method for labeling objects; [0033]: the device for labeling objects; [0038]: UAV; the drone 100 communicates with the driver assistance device 200 via the network 300; [0053]: one panoramic optical camera is disposed on one side of the propeller of the drone 100 to acquire images of the sky), comprising a memory, a processor and a computer program stored in the memory and capable of running, wherein the processor, when executing the program, implements steps of a target labeling method, wherein the target labeling method comprises ([0043]: the memory 211, memory controller 212, processor 213, peripheral interface 214, input/output unit 215, display unit 217, and communication unit 219 are electrically connected to each other directly or indirectly to realize data transmission or interaction; the processor 213 executes executable modules stored in the memory 211, such as the software function modules and computer programs included in the object annotation device 220):
The rest claim limitations are similar to claim limitations recited in claim 1. Therefore, same rational used to reject claim 1 is also used to reject claim 15.
Regarding to claim 16 (Original), Teng Long in view of Yang and Bar-Nahum discloses the electronic device according to claim 15,
The rest claim limitations are similar to claim limitations recited in claim 2. Therefore, same rational used to reject claim 2 is also used to reject claim 16.
Regarding to claim 17 (Original), Teng Long in view of Yang and Bar-Nahum discloses the electronic device according to claim 15, wherein the method further comprises:
The rest claim limitations are similar to claim limitations recited in claim 3. Therefore, same rational used to reject claim 3 is also used to reject claim 17.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hai Tao Sun whose telephone number is (571)272-5630. The examiner can normally be reached 9:00AM-6:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Daniel Hajnik can be reached at 5712727642. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAI TAO SUN/Primary Examiner, Art Unit 2616
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