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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/17/2025 has/have been considered by the examiner.
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.
Claim(s) 1-2, 8, 14-15 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al (CN 107804227 A), hereinafter Zhou in view of Shen et al (CN 114011066 A), hereinafter Shen.
-Regarding claim 1, Zhou discloses a method for generating a human body depth map, applied to an electronic device, the method comprising (Abstract; FIGS. 1-9): acquiring a skeletal point position of each skeletal point in a skeleton of a target object in a two-dimensional image coordinate system (FIG. 1, human skeleton calculation module; FIG. 9; Page 2, last paragraph, “… extracting … according to coordinate values … human body skeleton”; Page 3, 3rd paragraph, “… in the human region of image grabbing multiple skeleton points … form complete human skeleton diagram …”, 4th paragraph), and acquiring a distance from each skeletal point to a camera imaging plane in a three-dimensional camera coordinate system (Page 2, last paragraph, “…distance … of skeleton …”; Page 3, 2nd paragraph, “obtain each coordinate value of the light point (x, y, z) … z … is the depth value”; ); determining a depth value of each first pixel point of the skeleton based on the skeletal point position and the distance of each skeletal point; and obtaining a human body depth map of the target object (FIGS. 1, 4, 7-9; Table 1; Page 3, 2nd paragraph; 3nd paragraph, “… z-value in the point set range is set to form the foreground depth map and the foreground depth map constructing human body region image …”, 4th paragraph; Page 5, last paragraph – page 6, 2nd paragraph).
Zhou does not disclose a blank canvas for drawing a depth map.
In the same field of endeavor, Shen teaches a visual sensor for robot simulation test environment (Shen: Abstract; FIGS. 1-2). Shen further teaches a blank canvas for drawing a depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph, “establishing a canvas component … assigning the obtained depth visible domain pixel to the canvas component … returning the corresponding canvas … the generated depth image”).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Zhou with the teaching of Shen by using a canvas in order to have an optimized display effect on the human body depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph).
-Regarding claim 14, Zhou discloses an apparatus for generating a human body depth map, comprising: a memory, configured to store computer-executable instructions; and a processor, configured to (one or more memories and processors must be used in order implement the system shown in FIG. 1), when executing the computer-executable instructions stored in the memory, implement (Abstract; FIGS. 1-9): acquiring a skeletal point position of each skeletal point in a skeleton of a target object in a two-dimensional image coordinate system (FIG. 1, human skeleton calculation module; FIG. 9; Page 2, last paragraph, “… extracting … according to coordinate values … human body skeleton”; Page 3, 3rd paragraph, “… in the human region of image grabbing multiple skeleton points … form complete human skeleton diagram …”, 4th paragraph), and acquiring a distance from each skeletal point to a camera imaging plane in a three-dimensional camera coordinate system (Page 2, last paragraph, “…distance … of skeleton …”; Page 3, 2nd paragraph, “obtain each coordinate value of the light point (x, y, z) … z … is the depth value”; ); determining a depth value of each first pixel point of the skeleton based on the skeletal point position and the distance of each skeletal point; and obtaining a human body depth map of the target object (FIGS. 1, 4, 7-9; Table 1; Page 3, 2nd paragraph; 3nd paragraph, “… z-value in the point set range is set to form the foreground depth map and the foreground depth map constructing human body region image …”, 4th paragraph; Page 5, last paragraph – page 6, 2nd paragraph).
Zhou does not disclose a blank canvas for drawing a depth map.
In the same field of endeavor, Shen teaches a visual sensor for robot simulation test environment (Shen: Abstract; FIGS. 1-2). Shen further teaches a blank canvas for drawing a depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph, “establishing a canvas component … assigning the obtained depth visible domain pixel to the canvas component … returning the corresponding canvas … the generated depth image”).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Zhou with the teaching of Shen by using a canvas in order to have an optimized display effect on the human body depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph).
-Regarding claim 20, Zhou discloses a non-transitory computer-readable storage medium, having computer-executable instructions stored therein, the computer-executable instructions, when executed by a processor, causing the processor to implement (Abstract; FIGS. 1-9; one or more memories and processors must be used in order implement the system shown in FIG. 1): acquiring a skeletal point position of each skeletal point in a skeleton of a target object in a two-dimensional image coordinate system (FIG. 1, human skeleton calculation module; FIG. 9; Page 2, last paragraph, “… extracting … according to coordinate values … human body skeleton”; Page 3, 3rd paragraph, “… in the human region of image grabbing multiple skeleton points … form complete human skeleton diagram …”, 4th paragraph), and acquiring a distance from each skeletal point to a camera imaging plane in a three-dimensional camera coordinate system (Page 2, last paragraph, “…distance … of skeleton …”; Page 3, 2nd paragraph, “obtain each coordinate value of the light point (x, y, z) … z … is the depth value”; ); determining a depth value of each first pixel point of the skeleton based on the skeletal point position and the distance of each skeletal point; and obtaining a human body depth map of the target object (FIGS. 1, 4, 7-9; Table 1; Page 3, 2nd paragraph; 3nd paragraph, “… z-value in the point set range is set to form the foreground depth map and the foreground depth map constructing human body region image …”, 4th paragraph; Page 5, last paragraph – page 6, 2nd paragraph).
Zhou does not disclose a blank canvas for drawing a depth map.
In the same field of endeavor, Shen teaches a visual sensor for robot simulation test environment (Shen: Abstract; FIGS. 1-2). Shen further teaches a blank canvas for drawing a depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph, “establishing a canvas component … assigning the obtained depth visible domain pixel to the canvas component … returning the corresponding canvas … the generated depth image”).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Zhou with the teaching of Shen by using a canvas in order to have an optimized display effect on the human body depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph).
-Regarding claims 2 and 15, Zhou in view if Shen teaches the method of claim 1 and the apparatus of claim 14.
Zhou does not disclose a blank canvas for drawing a depth map having the target resolution.
In the same field of endeavor, Shen teaches a visual sensor for robot simulation test environment (Shen: Abstract; FIGS. 1-2). Shen further teaches a blank canvas a blank canvas for drawing a depth map having the target resolution (Shan: Page 4, Sec. Step 230:, 7th paragraph, “establishing a canvas component according to the resolution determined in step 102, obtaining the canvas component with consistent resolution, assigning the obtained depth visible domain pixel to the canvas component … returning the corresponding canvas … the generated depth image”).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Zhou with the teaching of Shen by using a canvas in order to have an optimized display effect on the human body depth map (Shan: Page 4, Sec. Step 230:, 7th paragraph).
-Regarding claim 8, Zhou in view if Shen teaches the method of claim 1. The combination further teaches based on the depth value of each first pixel point to obtain a skeletal depth map; and based on the depth value of each first pixel point, a second pixel point in a region other than each first pixel point in the skeletal depth map, to obtain the human body depth map of the target object (Zhou: Page 3, 2nd – 3rd paragraphs).
Allowable Subject Matter
Claims 3-7, and 9-13, and 16-19 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Peng et al (2008 10th International Conference on Control, Automation, Robotics and Vision), hereinafter Peng teaches a method for estimating human skeleton proportions automatically from two-dimensional (2D) joint locations extracted from a monocular video and determining depth information of a certain reference joint on the human skeleton.
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/XIAO LIU/Primary Examiner, Art Unit 2664
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