Patent Application 18176076 - INFORMATION PROCESSING APPARATUS METHOD AND MEDIUM - Rejection

Patent Application 18176076 - INFORMATION PROCESSING APPARATUS METHOD AND MEDIUM

Title: INFORMATION PROCESSING APPARATUS, METHOD AND MEDIUM

Application Information

• Invention Title: INFORMATION PROCESSING APPARATUS, METHOD AND MEDIUM
• Application Number: 18176076
• Submission Date: 2025-05-15T00:00:00.000Z
• Effective Filing Date: 2023-02-28T00:00:00.000Z
• Filing Date: 2023-02-28T00:00:00.000Z
• National Class: 382
• National Sub-Class: 107000
• Examiner Employee Number: 98744
• Art Unit: 2668
• Tech Center: 2600

Rejection Summary

• 102 Rejections: 0
• 103 Rejections: 4

Cited Patents

No patents were cited in this rejection.

Office Action Text

    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
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in Japan on 3/29/2022. It is noted, however, that applicant has not filed a certified copy of the JP2022-53262 application as required by 37 CFR 1.55.

Claim Rejections - 35 USC § 103
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 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 nonobviousness.

Claim(s) 1, 3, and 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1).

Regarding claim 1, Khan et al teaches an information processing device comprising a processor to: acquire, based on a plurality of captured images acquired by performing image capture while varying a positional relationship between an imaging subject and an imaging position (3.3, Page 3, we can find the motion of the camera (if present), then treated on the basis of this situation, and we may use another algorithm, to cover only the foreground object motion. i.e. imaging subject (camera) has motion, and determine relationship between camera motion and foreground. Algorithms performed in field of computer vision with a processing unit such as a computer), 
a motion magnitude for each of a plurality of image elements constituting the captured images on the images of the imaging subject (3.3, Page 3, the motion vectors for each macro-block are calculated from where magnitude of the motion is used to separate background and foreground. i.e. motion magnitude determined for image elements); 
create the histogram with respect to image elements, among the plurality of image elements, (3.6 and Page 4, the overall histogram of the proposed algorithm is created, so that x-axis has motion vectors magnitude (in 32 values) and y-axis has the number of blocks of size (4 × 4) having motion in that range (total bins are 32), which is used for decision-making of a threshold value. i.e. creating a histogram based on the image elements (blocks)); 
refer to the histogram in order to estimate a motion magnitude range corresponding to image elements capturing a predetermined part of the imaging subject, the predetermined part being within a predetermined distance range of the imaging position (3.7.1 and Page 4, if there is one largest peak and lies in the first bin, as shown in Fig. 2, this shows that maximum numbers of blocks are stationary, so it is considered as background. The largest peak in the first bin belongs to stationary part of the frame. It means that most of the blocks are stationary, and hence, this forms stationary background and anything else, if any, is foreground. i.e. estimate a motion magnitude range corresponding to elements capturing a predetermined part of the imaging subject (foreground or background) which correspond to the distance range of the imaging position); 
and specify the image elements capturing the predetermined part, among the plurality of image elements constituting the captured images, by specifying the image elements belonging to the estimated motion magnitude range (3.7.1-3.7.3 and Page 4-5, image elements (foreground or background) are specified by specifying the elements that belong to the estimated motion magnitude range (within the thresholds shown in equations 8 and 9)).  
Khan et al does not teach determine a threshold used to exclude image elements not to be included in a histogram showing a distribution of the motion magnitudes of the plurality of image elements based on the motion magnitudes of the image elements; 
and excluding image elements having motion magnitudes that exceed the threshold (as can be seen by the strikethrough above).
In a similar field of endeavor, Choudhury et al teaches determine a threshold used to exclude image elements not to be included in a histogram showing a distribution of the motion magnitudes of the plurality of image elements based on the motion magnitudes of the image elements; and excluding image elements having motion magnitudes that exceed the threshold (as can be seen by the strikethrough above) (Para 63, the spatial distribution of initial (e.g., per-pixel, per-pixel-block, etc.) motion characteristics in each of the foreground objects (202) to generate a histogram of per-pixel texture values for each such foreground object. Outliers in the histogram such as initial (e.g., per-pixel, per-pixel-block, etc.) motion characteristics above a initial (e.g., per-pixel, per-pixel-block, etc.) motion characteristic threshold for foreground objects may be removed from the spatial distribution of initial (e.g., per-pixel, per-pixel-block, etc.) motion characteristics in each such foreground object. i.e. outliers in the histogram may be removed from the spatial distribution of a foreground object based on a motion characteristic threshold. The motion magnitude threshold, as seen in Para 63, can be determined as a relative value among histogram bins of the histogram);
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) so that a threshold is determined to parse data before creating a histogram. Doing so would allow the system to detect motion dragging artifacts for dynamic adjustment of frame rate conversion settings, and more specifically, remove outliers (Para 2 and Para 63, Choudhury et al).


Regarding claim 3, Khan et al teaches the information processing device according to claim 1, wherein the processor specifies a motion magnitude section of the histogram in which the distribution is concentrated, and estimates the motion magnitude range based on the specified motion magnitude section (3.7.1-3.7.3 and Page 4-5, image elements (foreground or background) are determined by first determining where the largest magnitude peaks are (distribution is concentrated) and then determining the motion magnitude range based on the peaks (see different situations for determining peaks in association with thresholds in Figures 2-4))).

Regarding claim 8, claim 8 rejected for the same reasons as claim 1 in the combination above.
 
Regarding claim 9, claim 9 rejected for the same reasons as claim 1 in the combination above.


Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and further in view of Zhou et al., (US 20210133996 A1).

Regarding claim 2, Khan et al and Choudhury et al do not teach, the information processing device according to claim 1, wherein the processor specifies a location where variation in the motion magnitude exceeds a predetermined reference when the image elements are arranged in order of the motion magnitude, and determines a motion magnitude corresponding to the specified location as the threshold.
In a similar field of endeavor, Zhou et al teaches the information processing device according to claim 1, wherein the processor specifies a location where variation in the motion magnitude exceeds a predetermined reference when the image elements are arranged in order of the motion magnitude, and determines a motion magnitude corresponding to the specified location as the threshold (Fig 6 and Para 100, if the magnitude of a threshold percentage of these vectors (e.g., 30%, 50% or other value) is greater than a magnitude threshold then the ROI can be considered to be moving. i.e. specifies a location where variation in then motion magnitude exceeds a predetermined reference when the elements are arranged in order of motion magnitude, Fig 6 604  shows percentage of vectors that has magnitude less than or equal to predetermined magnitude A).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of over Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and Zhou et al., (US 20210133996 A1) so that the processor specifies a location where variation in the magnitude exceeds a predetermined reference when the image elements are arranged in order of the motion magnitude. Doing so would allow for collecting and utilizing real-world depth information for an object of interest to more accurately analyze the movement of those objects in an image plane (Para 24, Zhou et al).



Claim(s) 4-5, and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and further in view of Matsuzaki (JP 2020182048 A).

Regarding claim 4, Khan et al and Choudhury et al do not teach, the information processing device according to claim 1, the processor further acquires a connected image capturing a wider range than a range that can be captured at one time from a single imaging position by connecting the plurality of captured images so that the image elements specified by the processor and included in each of the plurality of captured images are aligned.
In a similar field of endeavor, Matsuzaki teaches, the information processing device according to claim 1, the processor further acquires a connected image capturing a wider range than a range that can be captured at one time from a single imaging position by connecting the plurality of captured images so that the image elements specified by the processor and included in each of the plurality of captured images are aligned (Para 10, according to such a configuration or method, when the photographing device is moved by a moving body, images in a shooting target range wider than the shooting range can be obtained as each shot image from a distance where an appropriate resolution is secured. Then, by arranging the captured images captured in this way, it is possible to acquire a panoramic image which is a wide area image having an appropriate resolution).  
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and Matsuzaki (JP 2020182048 A) so that the processor acquires a connected image capturing a wider range than a range that can be captured form a single imaging position. Doing so would allow for an image processing device capable of acquiring a panoramic image of a shooting target wider than the shooting range of a camera with an appropriate resolution (Para 6, Matsuzaki).
	
Regarding claim 5, Khan et al and Choudhury et al do not teach, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies while maintaining a substantially constant distance from the predetermined part of the imaging subject.
In a similar field of endeavor, Matsuzaki teaches, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies while maintaining a substantially constant distance from the predetermined part of the imaging subject (Para 11, from each photographed image captured by the photographing apparatus moved by the moving body, the target photographed object is extracted based on having a specific velocity vector in the image. As a result, it is possible to extract information necessary for specifying the relative position from the captured image without performing image processing for separating the imaging target from the background with high accuracy. i.e. capturing image while maintaining a substantially constant distance from the predetermined part).  
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and Matsuzaki (JP 2020182048 A) so that the processor includes performing image capturing on a flying object while staying at a substantially constant distance from the predetermined part of the imaging subject. Doing so would allow for an image processing device capable of acquiring a panoramic image of a shooting target wider than the shooting range of a camera with an appropriate resolution (Para 6, Matsuzaki).

Regarding claim 7, Khan et al and Choudhury et al do not teach, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies substantially vertically while facing one side face of a construction serving as the imaging subject.
In a similar field of endeavor, Matsuzaki teaches, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies substantially vertically while facing one side face of a construction serving as the imaging subject (Para 90 and Fig. 9, the mobile photographing apparatus 20 has a field of view E when arranged at a distance L at which a photographed image of the wall surface 101 of the building 100 can be obtained with a predetermined resolution. The wall surface 101 of the building 100 is wider than 1 times in the horizontal direction and wider than 1 times in the vertical direction with respect to the range of the captured image that can be taken in the field of view E. Therefore, the moving photographing device 20 moves a position at a distance L from the wall surface 101 of the building 100, and creates a plurality of captured images so that an image of the wall surface 101 of the building 100 can be obtained with a predetermined resolution. R2 is set. i.e. performing using capture using an imaging device that flies substantially vertically while facing one side face of a construction).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and Matsuzaki (JP 2020182048 A) so that the processor includes capturing images using a flying device that flies substantially vertically while facing on side of a construction serving as the imaging subject. Doing so would allow for an image processing device capable of acquiring a panoramic image of a shooting target wider than the shooting range of a camera with an appropriate resolution (Para 6, Matsuzaki).


Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and further in view of Henry et al., (US  A1).

Regarding claim 6, Khan et al and Choudhury et al do not teach, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies while maintaining a substantially constant speed during image capture.
In a similar field of endeavor, Henry et al teaches, the information processing device according to claim 1, wherein the plurality of captured images are captured images acquired by performing image capture using an imaging device provided on a flying object that flies while maintaining a substantially constant speed during image capture (Para 51, the UAV 102 may determine a maximum constant speed for the portion of the scan target 111 with the lowest light level, and may use that speed as the constant image capture speed for the entire scan).
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date to incorporate the teachings of Khan et al., (NPL: Foreground detection using motion histogram threshold algorithm in high-resolution large datasets) in view of Choudhury et al., (US 20190180454 A1) and Henry et al., (US 20230142394 A1) so that the flying object stays at a mostly constant speed while imaging. Doing so would allow the system to capture images from vantage points that would otherwise be difficult to reach, and to allow for an improvement while capturing a target object at a desired distance and accuracy of coverage which can be tedious for a human pilot (Para 1, Henry et al).

Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US-20180020164-A1
US-20170237904-A1
US-20130011069-A1
US-20120169937-A1
US-20110044664-A1
US-11100655-B2

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/JACK PETER KRAYNAK/Examiner, Art Unit 2668                                                                                                                                                                                                        
/VU LE/Supervisory Patent Examiner, Art Unit 2668