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 .
Response to Arguments
112 Rejections
Based on applicant’s clarifying amendments and comments, the previously set forth rejections have been overcome.
102 Rejections
Applicant’s arguments, see pages 8-9, filed 4/16/26, with respect to the rejection(s) of claim(s) 1-15 and 17-21 under 35 USC § 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Hamaya et al. (JP 2013156912A).
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.
Claim(s) 1-4, 6-15 and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yonekawa et al. (2018/0195973) in view of Hamaya et al. (JP 2013156912A).
With respect to claim 1, Yonekawa et al. teaches a method performed by a user equipment (i.e. an outboard camera 21 of vehicle 20 having computer elements 1 and 2; [0035]), comprising: capturing a video stream of a road (as Yonekawa et al. teaches the camera 21 captures moving images during a driving operation of a vehicle; [0035] [0040]); and transmitting at least part of the video stream to a server (113; as Yonekawa et al. teaches at least image data captured from the video stream is sent to a web server; [0059] [0310]), wherein a first video clip (i.e. as an image from the video) from the captured video (via 21) from the at least part of the video stream is compared with a second video clip (i.e. a previously collected image).
Yonekawa et al. remains silent regarding to determine a vibration reflecting a quality of a road section of the road, wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip.
Hamaya et al. teaches using a camera (54/55; [0017]) to collect video clips representative to road quality [0067-0068]. The camera (54/55) is used to determine a vibration reflecting a quality of a road section of the road (as in case B taught in [0030], Hamaya et al. teaches comparing and analyzing differences between captured moving images to perform deterioration determinations, which cause vibrations creating the differences between the video clips), wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip (i.e. as Hamaya et al. teaches by using the difference between clips analyzes the differences between current and past footage. Since the fixed camera’s historical state is stored, it allows for automatically detecting vibrations caused by the deterioration.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify the method of Yonekawa et al. by integrating the teachings of Hamaya et al. Specifically, it would have been obvious to utilize collected video clips to determine a difference representing road damage causing vibrations. One of ordinary skill in the art would have been motivated to do so because Hamaya et al. teaches that this modification streamlines repairs by directly sending appropriate personnel and repair instructions. This substitution of techniques would yield predictable results, improving the efficiency of the Yonekawa method.
With respect to claims 2 and 18, Yonekawa et al. as modified teaches the method wherein the second video clip (i.e. the previous collected image) is a reference video clip used as a quality baseline of the road section (the previously collected image serves as a historical baseline for calculating the differences between the clips, as modified, thereby providing a quality baseline for monitoring changes in road quality).
With respect to claims 3 and 19, Yonekawa et al. as modified teaches the method wherein the second video clip (i.e. the previously collected image) corresponds to the road section (i.e. the portion of the road having the crack) with a quality equal to a predefined level (as the second image defines the quality of the road in the past, thereby defining a predefined level from a previous time, as Yonekawa et al. teaches in [0170] using that past image to define a previous road quality to determine if the quality of the road at that present moment is better or worse).
With respect to claim 4 and 20, Yonekawa et al. as modified teaches the method wherein the user equipment is a vehicle (20 having camera 21), and the second video clip (i.e. past image) is associated with a type of the vehicle (as the image is collected from the same vehicle, thereby being the same type).
With respect to claim 6, Yonekawa et al. as modified teaches the method wherein when the vibration matches a vibration pattern, the vibration indicates a potential damage of the road section (as the calculated difference, as modified, indicates a growing crack creating a change in vibrations and thereby matching a vibration pattern indicating a growing crack; insofar as what is structurally recited, as there is not active steps performing a matching operation to stored vibrational patterns).
With respect to claim 7, Yonekawa et al. as modified teaches the method wherein the vibration pattern includes one video offset within a predefined range (as the calculated difference, as modified, is calculated from images collected in the present and the past).
With respect to claim 8, Yonekawa et al. as modified teaches the method wherein the first video clip is determined by the user equipment (Yonekawa teaches camera 21 determines the first video clip by collecting those images).
With respect to claim 9, Yonekawa et al. as modified teaches the method wherein the first video clip (i.e. image collected by the camera 21) is determined according to the user equipment entering (21) entering and/or leaving the road section (as the camera determines the clip when the vehicle is entering and/or leaving the road section containing the crack; insofar as what is structurally recited).
With respect to claim 10, Yonekawa et al. as modified teaches the method wherein the comparison between the first video clip and the second video clip (as the examiner considers the difference calculation to be the comparison) is based at least in part on a trajectory of the user equipment (i.e. direction of the camera 21; [0035]).
With respect to claim 11, Yonekawa et al. as modified teaches the method further comprising: receiving a notification from the server (113), wherein the notification (as a display 112 displays a notification) indicates a potential damage of the road section (as Yonekawa et al. teaches displaying the potential damage of the road section by superimposing the determine cracks; [0086]).
With respect to claim 12, Yonekawa et al. teaches all that is claimed further defining the alternative selected by the examiner in claim 11. Therefore, the limitations of claim 12 do not further limit the examiner elected alterative seen in claim 11 over the prior art.
With respect to claim 13, Yonekawa et al. teaches the method wherein the server (113) is located at the user equipment (20/21).
With respect to claim 14, Yonekawa et al. teaches a user equipment (1/2/20/21), comprising: one or more processors (as indirectly taught, as the disclosed invention in Yonekawa operates in a computer environment); and one or more memories [0184] comprising computer program codes [0314], the one or more memories [0184] and the computer program codes [0314] configured to, with the one or more processors (as indirectly taught, as the disclosed invention in Yonekawa operates in a computer environment), cause the user equipment (1/2/20/21) at least to capture a video stream of a road (as Yonekawa et al. teaches the camera 21 captures moving images during a driving operation of a vehicle; [0035] [0040]); and transmit at least part of the video stream to a server (113; as Yonekawa et al. teaches at least image data related to a pavement crack analysis is sent to a web server; [0059] [0310]), wherein a first video clip (i.e. as an image) from the captured video (via 21) from the at least part of the video stream is compared with a second video clip (i.e. a previously collected image).
Yonekawa et al. remains silent regarding to determine a vibration reflecting a quality of a road section of the road, wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip.
Hamaya et al. teaches using a camera (54/55; [0017]) to collect video clips representative to road quality [0067-0068]. The camera (54/55) is used to determine a vibration reflecting a quality of a road section of the road (as in case B taught in [0030], Hamaya et al. teaches comparing and analyzing differences between captured moving images to perform deterioration determinations, which cause vibrations creating the differences between the video clips), wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip (i.e. as Hamaya et al. teaches by using the difference between clips analyzes the differences between current and past footage. Since the fixed camera’s historical state is stored, it allows for automatically detecting vibrations caused by the deterioration.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify the method of Yonekawa et al. by integrating the teachings of Hamaya et al. Specifically, it would have been obvious to utilize collected video clips to determine a difference representing road damage causing vibrations. One of ordinary skill in the art would have been motivated to do so because Hamaya et al. teaches that this modification streamlines repairs by directly sending appropriate personnel and repair instructions. This substitution of techniques would yield predictable results, improving the efficiency of the Yonekawa method.
With respect to claim 15, Yonekawa et al. as modified teaches the user equipment (1/2/20/21) according to claim 14, wherein the one or more memories [0184] and the computer program codes [0314] are configured to, with the one or more processors (as indirectly taught), cause the user equipment (1/2/20/21) to perform further observations comprising: receive a notification from the server (113), wherein the notification (as a display 112 displays a notification) indicates a potential damage of the road section (as Yonekawa et al. teaches displaying the potential damage of the road section by superimposing the determine cracks; [0086]).
With respect to claim 17, Yonekawa et al. teaches a method performed by a server (i.e.1/2 as these elements are disclosed as being a variety of computing elements, including a server; [0182]), comprising: receiving at least part of a video stream captured for a road from a user equipment (as Yonekawa et al. teaches the camera 21 captures moving images during a driving operation of a vehicle; [0035] [0040]); and determining a quality of a road section of the road, by comparing a first video clip (i.e. an image) from the at least part of the video stream with a second video clip.
Yonekawa et al. remains silent regarding determining a vibration reflecting a quality of a road section of the road, wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip.
Hamaya et al. teaches using a camera (54/55; [0017]) to collect video clips representative to road quality [0067-0068]. The camera (54/55) is used to determine a vibration reflecting a quality of a road section of the road (as in case B taught in [0030], Hamaya et al. teaches comparing and analyzing differences between captured moving images to perform deterioration determinations, which cause vibrations creating the differences between the video clips), wherein the vibration includes one or more video offsets of the first video clip relative to the second video clip (i.e. as Hamaya et al. teaches by using the difference between clips analyzes the differences between current and past footage. Since the fixed camera’s historical state is stored, it allows for automatically detecting vibrations caused by the deterioration.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to modify the method of Yonekawa et al. by integrating the teachings of Hamaya et al. Specifically, it would have been obvious to utilize collected video clips to determine a difference representing road damage causing vibrations. One of ordinary skill in the art would have been motivated to do so because Hamaya et al. teaches that this modification streamlines repairs by directly sending appropriate personnel and repair instructions. This substitution of techniques would yield predictable results, improving the efficiency of the Yonekawa method.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shimomura et al. (2013/0169794) which teaches image data related to road quality.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW G MARINI whose telephone number is (571)272-2676. The examiner can normally be reached Monday-Friday 8am-5pm.
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/MATTHEW G MARINI/Primary Examiner, Art Unit 2853
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