DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/07/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Taieb et al. (US 20210372808 A1) in view of Chaurasia et al. (US 20180374217 A1).
Concerning claim 1, Taieb et al. (hereinafter Taieb) teaches a method of driving operation, comprising:
receiving, by a computer located in a vehicle, a first image frame and a second image frame from a camera located on or in the vehicle (¶¶0109-0110: embodiments consisting of a single image capture device; figs. 5A-5C: multi-frame analysis; ¶0168, ¶0172, ¶0177: consecutive frames (i.e., at least a first image frame and a second image frame)), wherein the first image frame is received prior to the second image frame (¶0168, ¶0172, ¶0177: consecutive frames implies one frame comes after the other; ¶0512: …the second image may be captured at some time after the first image);
determining a first set of characteristics about a first set of pixels in the first image frame and a second set of characteristics about a second set of pixels in the second image frame (figs. 5A-5C: multi-frame analysis; ¶¶0176-0177: Tracking detected segments across consecutive image frames and accumulating frame-by-frame data associated with detected segments; figs. 39A-39B; ¶¶0511-0512: identifying non-semantic features in a first image and analyzing a second image to identify a representation of the non-semantic features.);
obtaining a motion information for each pixel in the second set of pixels by comparing the second set of characteristics about the second set of pixels with the first set of characteristics about the first set of pixels (figs. 5A-5C: multi-frame analysis; ¶0168: camera motion between consecutive image frames and calculate the disparities in pixels between the frames; ¶0174: optical flow analysis to identify motion);
generating a combined set of characteristics associated with each pixel in the second set of pixels and each pixel from the first set of pixels (¶0194: The processed information corresponding to the analysis of the first, second, and/or third plurality of images may be combined. The processed information includes what is depicted in figs. 5A-5B & 6 and may include motion information, road hazard information, object information (e.g., pedestrian, vehicle, etc.), road information (e.g., road marks and/or lane geometry) and/or object color analysis information);
determining attributes of a road on which the vehicle is operating using at least some of the combined set of characteristics (¶0168: road hazards and road surface; ¶¶0175-0177: road marks and/or lane geometry); and
causing the vehicle to perform a driving related operation in response to the determining the attributes of the road (¶0169; ¶0177: processing unit 110 may cause one or more navigational responses in vehicle). Not explicitly taught is generating, using the motion information for each pixel in the second set of pixels, a combined set of characteristics associated with each pixel in the second set of pixels and each pixel from the first set of pixels.
Chaurasia et al. (hereinafter Chaurasia), in a similar field of endeavor, teaches a tracking system and method, wherein a combined set of characteristics associated with each pixel in the second set of pixels and each pixel from the first set of pixels is generated using the motion information for each pixel in the second set of pixels (¶0007; ¶0011; ¶0015; ¶0025 : when tracking a ball, characteristics of the ball blob from the first frame and the second frame are combined when the predicted location of one of the tracks lies within one of the second blobs). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the teachings of Taieb and Chaurasia by using motion information for each pixel in the second set of pixels to generate a combined set of characteristics associated with each pixel in the second set of pixels and each pixel from the first set of pixels in order to provide much more consistent spatial characteristics for further processing (Chaurasia, ¶0055).
Concerning claim 2, Taieb further teaches the method of claim 1, wherein the obtaining the motion information for each pixel in the second set of pixels includes:
determining, for each pixel in the second set of pixels, an extent to which a characteristic of a pixel in the second set of pixels has moved relative to a same characteristic of a corresponding pixel in the first set of pixels, wherein the motion information of the pixel indicates the extent to which the characteristic the pixel has moved from the first image frame to the second image frame (¶0168: …processing unit 110 may estimate camera motion between consecutive image frames and calculate the disparities in pixels between the frames…; ¶0174: optical flow analysis).
Concerning claim 3, Chaurasia further teaches wherein the combined set of characteristics is generated for each pixel in the second set of pixels by:
determining, for each pixel in the second set of pixels, that one pixel corresponds to another pixel in the first set of pixels using the motion information for the one pixel (¶0007; ¶0011; ¶0015); and
generating the combined set of characteristics for each pixel in the second set of pixels by combining, for each pixel in the second set of pixels, one or more characteristic of the one pixel in the second set of pixels with one or more characteristic of the another pixel in the first set of pixels (¶0007; ¶0011; ¶0015).
Concerning claim 4, Taieb further teaches the method of claim 1, wherein the determining the attributes of the road using the at least some of the combined set of characteristics comprises:
determining, for each pixel in the second set of pixels, a category of information associated with a pixel (¶0162).
Concerning claim 5, Taieb further teaches the method of claim 4, wherein the category of information includes a road, a terrain, a plantation, a vehicle, a traffic light, or a person (¶0162).
Concerning claim 6, Taieb further teaches the method of claim 1, wherein the determining the attributes of the road using the at least some of the combined set of characteristics comprises:
determining, for each pixel in the second set of pixels and by using the combined set of characteristics for each pixel in the second set of pixels, whether a pixel is associated with a lane marker of a lane on the road (¶¶0175-0177).
Concerning claim 7, Taieb further teaches the method of claim 1, wherein the determining the first set of characteristics and the second set of characteristics include determining, for each pixel in the first image frame, the first set of characteristics, and determining, for each pixel in the second image frame, the second set of characteristics (¶¶0511-0512).
Claim 8 is the corresponding apparatus to the method of claim 1 and is rejected under the same rationale. Taieb further teaches a system including processors that perform the functions of the invention (figs. 1-2F; ¶0096).
Concerning claim 9, Taieb further teaches the apparatus of claim 8, wherein the first image frame is received immediately prior to the second image frame (¶0168, ¶0172, ¶0177: consecutive frames (i.e., at least a first image frame and a second image frame); ¶¶0511-0512).
Concerning claim 10, Taieb further teaches the apparatus of claim 8, wherein the first set of characteristics and the second set of characteristics include a color for each pixel in the first set of pixels and the second set of pixels, respectively (¶0179: color analysis across consecutive frames; ¶0504: color-based detection algorithms).
Concerning claim 11, Taieb further teaches the apparatus of claim 8, wherein the first set of characteristics and the second set of characteristics include a shape for each pixel in the first set of pixels and the second set of pixels, respectively (¶¶0171-0173; ¶0179).
Concerning claim 12, Taieb further teaches the apparatus of claim 8, wherein the first set of characteristics and the second set of characteristics include a texture for each pixel in the first set of pixels and the second set of pixels, respectively (¶¶0171-0173; ¶0179).
Concerning claim 13, Taieb further teaches the apparatus of claim 8, wherein the first set of pixels include a plurality of pixels from the first image frame (figs. 5A-5C: multi-frame analysis; ¶¶0176-0177: Tracking detected segments across consecutive image frames and accumulating frame-by-frame data associated with detected segments; figs. 39A-39B).
Concerning claim 14, Taieb further teaches the apparatus of claim 8, wherein the second set of pixels include a plurality of pixels from the second image frame (figs. 5A-5C: multi-frame analysis; ¶¶0176-0177: Tracking detected segments across consecutive image frames and accumulating frame-by-frame data associated with detected segments; figs. 39A-39B).
Claim 15 is the corresponding non-transitory computer readable program storage medium to the method of claim 1 and is rejected under the same rationale. Taieb further teaches non-transitory computer-readable storage media that store program instructions to perform the functions of the invention (¶0021).
Concerning claim 16, Taieb further teaches the non-transitory computer readable program storage medium of claim 15, wherein the determining the attributes of the road using the at least some of the combined set of characteristics comprises:
determining, using the at least some of the combined set of characteristics, locations of corner points of lane markers of a lane on which the vehicle operates on the road (¶¶0341-0343).
Concerning claim 17, Taieb further teaches the non-transitory computer readable program storage medium of claim 16, wherein the causing the vehicle to perform the driving related operation in response to the determining the attributes of the road comprises sending instructions to a motor in a steering system of the vehicle, wherein the instructions cause the motor to steer the vehicle along the lane using the locations of the corner points of the lane markers (¶¶0341-0343; ¶0350).
Concerning claim 18, Taieb further teaches the non-transitory computer readable program storage medium of claim 15, wherein the determining the attributes of the road using the at least some of the combined set of characteristics comprises:
determining, using the at least some of the combined set of characteristics, a presence of traffic cones on the road (¶¶0490-0491: determining road features including traffic cones); and
determining, in response to the determining the presence of the traffic cones, locations of the traffic cones using the at least some of the combined set of characteristics (¶¶0490-0491: A location of the road features may be determined based on the captured images).
Concerning claim 19, Taieb further teaches the non-transitory computer readable program storage medium of claim 15, wherein the first set of pixels include all pixels from the first image frame (¶0168: calculating disparities in pixels between the consecutive frames).
Concerning claim 20, Taieb further teaches the non-transitory computer readable program storage medium of claim 15, wherein the second set of pixels include all pixels from the second image frame (¶0168: calculating disparities in pixels between the consecutive frames).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES M ANDERSON II whose telephone number is (571)270-1444. The examiner can normally be reached Monday - Friday 10AM-6PM.
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/James M Anderson II/Primary Examiner, Art Unit 2425