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 .
DETAILED ACTION
Following prior arts found to be relevant to applicant’s invention during current search
US20110074926 A1 (hereinafter Khan)
US 20140294361 A1 (hereinafter Acharya)
US 20010043738 A1 (Sawhney)
US 20030095711 A1 (Fig.1, 6: multi-camera pose estimation with foreknowledge)
US 20080262718 A1 (Fig.4, 5 multi-camera pose estimation with foreknowledge)
US 20100045701 A1 (Scott, para 49, describe camera based and sensor-based pose estimation are combined for higher accuracy: also see para 46-47, 5, 22-24)
Response to Remarks/Arguments
Double patenting rejection has been withdrawn in view of approved terminal disclaimer.
Applicant’s arguments with respect to claim prior art rejection have been fully considered but they are not persuasive for following reason.
Re: Prior art rejection of independent claims
Applicant argued in substance that prior art does not teach determining camera pose based on a first pose estimate based on image data and parallel second pose estimate based on sensor data, wherein the parallel second pose estimate is employed to verify the first pose estimate
Examiner respectfully disagrees and argues that Acharya teaches this. Acharya teaches “the geometry of the camera's view position and orientation, referred to herein as "pose" or "line-of-sight." {para 27}; “Both smartphone sensing and Computer Vision provide complimentary and orthogonal approaches for estimating video line-of-sigh. Exemplary embodiments of the present invention may therefore combine both approaches to provide high accuracy” {para 55}, para 57. Achrya describes two form of parallel camera pose/line-of-sight/orientation determination. One from the image data using SfM/computer vision {para 66, 55} and based on smartphone sensing {para 55}. These two techniques are combined {para 55, 66}. “input from gyroscope can be used to inform a hysteresis across multiple alignment attempts” {para 66}. “smartphone sensors are also valuable during alignment. GPS, compass, and accelerometer, can be used to estimate a rough camera pose. While these estimates may be prone to error, due substantial sources of noise in each sensor, they may be valuable to confirm outputs from SfM.” {para 69}. Therefore, two parallel estimates are used one is from video data using SfM/computer vision and another is from sensors to verify the SfM method
Therefore, applicant’s arguments are not persuasive
Re: Prior art rejection of dependent claims
Applicant has presented no additional argument, other than arguments already presented with respect to independent claims. Therefore, the arguments are similarly not persuasive.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1-5, 7-10, 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Khan in view of Acharya.
Regarding Claim 1. Khan teaches a method, comprising: receiving data from a plurality of cameras configured to capture a scene:[(Fig.1 para 36)] for each of the plurality of cameras, determining a relative pose of a given camera with respect to the scene for a frame based at least in part on sensor data associated with that camera for the frame [(para 36, “capturing devices can be equipped with one or more of a Global Positioning System (GPS) receiver, a gyroscope, accelerometer, a compass, etc., to obtain the location coordinates (latitude, longitude and altitude) and orientation information of the video capturing device. Moreover, the video capture device can determine the distance to the object being photographed with a rangefinder or from the camera zoom/focus information”. In para 47 “each frame may have different orientation, time, and location information. In these situations, adding metadata to individual frames can result in a more accurate measurement of the associated information.”; Fig.11A )] determining relative poses of cameras with respect to one or more other cameras comprising the plurality of cameras for the frame based on independently determined relative poses of individual cameras with respect to the scene for the frame:[(Fig.11B)] and generating at least a partial three-dimensional reconstruction of the scene for the frame based on received image data and determined relative camera poses for the frame. [(para 11)]
Khan does not explicitly show that the pose estimate is based on received image data and camera pose based on a first pose estimate based on image data and parallel second pose estimate based on sensor data, wherein the parallel second pose estimate is employed to verify the first pose estimate
However, in the same/related field of endeavor, Acharya teaches the pose estimate is based on received image data in addition to sensor data [(para 27, 66)]
And camera pose based on a first pose estimate based on image data and parallel second pose estimate based on sensor data, wherein the parallel second pose estimate is employed to verify the first pose estimate [( “the geometry of the camera's view position and orientation, referred to herein as "pose" or "line-of-sight." {para 27}; “Both smartphone sensing and Computer Vision provide complimentary and orthogonal approaches for estimating video line-of-sigh. Exemplary embodiments of the present invention may therefore combine both approaches to provide high accuracy” {para 55}, para 57. Acharya describes two form of parallel camera pose/line-of-sight/orientation determination. One from the image data using SfM/computer vision {para 66, 55} and based on smartphone sensing {para 55}. These two techniques are combined {para 55, 66}. “input from gyroscope can be used to inform a hysteresis across multiple alignment attempts” {para 66}. “smartphone sensors are also valuable during alignment. GPS, compass, and accelerometer, can be used to estimate a rough camera pose. While these estimates may be prone to error, due substantial sources of noise in each sensor, they may be valuable to confirm outputs from SfM.” {para 69}. Therefore, two parallel estimates are used one is from video data using SfM/computer vision and another is from sensors to verify the SfM method )]
Therefore, in light of above discussion it would have been obvious to one of the ordinary skill in the art, before the effective filing date of the claimed invention, to combine the teaching of the prior arts because such combination would enhance the pose estimation [(Acharya para 27, 66)]
Khan additionally teaches, with regards to claim 2. The method of claim 1, wherein the plurality of cameras is independently operated [(para 37)]
Khan additionally teaches, with regards to claim 3. The method of claim 1, wherein no foreknowledge exists of relative poses of cameras with respect to the scene and with respect to each other. [(the distance between is camera is determined from the obtained information {para 81, 37}, i.e. the distance and other pose was not known beforehand; the cameras are freely move anywhere and locations are based on freely roamed positions/pose para 53-63: and relative pose is determined {para 71} )]
Khan additionally teaches, with regards to claim 4. The method of claim 1, wherein relative poses of cameras with respect to the scene and with respect to each other are not fixed and are time variant. [(para 47, para 53-63)]:
Khan additionally teaches, with regards to claim 5. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises determining correspondences between images comprising the frame captured by the plurality of cameras [(para 73-74, 65)] .
Khan additionally teaches, with regards to claim 7. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises rectifying images comprising the frame captured by the plurality of cameras. [(para 44 compress decompress)]
Khan additionally teaches, with regards to claim 8. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises estimating depths in images comprising the frame captured by the plurality of cameras. [(para 69)]
Khan additionally teaches, with regards to claim 9. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises generating at least a corresponding portion of a point cloud for the frame.[[(para 59)]
Acharya additionally teaches, with regards to claim 10. The method of claim 1, wherein received data comprises image data ansensor dat. [(Acharya para 89)]
Acharya additionally teaches, with regards to claim 12. The method of claim 1, wherein the second pose estimate is employed to fill gaps in pose estimation when pose cannot be determined from the first estimate. [(Acharya para 68-69)]
Acharya additionally teaches, with regards to claim 13. The method of claim 1, wherein determined relative pose of a given camera with respect to the scene is with respect to features or fiducials of the scene. [(Acharya para 47, 62)]
Khan additionally teaches, with regards to claim 14. The method of claim 1, wherein data is received, relative poses are determined, and at least the partial three-dimensional reconstruction of the scene is generated for each of a plurality of times slices or frames.[[(Fig.9)]
Khan additionally teaches, with regards to claim 15. The method of claim 1, wherein received data comprises frames of a video recording of the scene. [(para 13)]
Khan in view of Acharya additionally teaches, with regards to claim 16. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame is based on synchronizing received data from the plurality of cameras that have captured different perspectives of the scene. [(Khan Fig.9; Acharya para 42)]
Acharya additionally teaches, with regards to claim 17. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame is based on correspondence between sets of features seen in common among multiple cameras. [(Acharya para 61-62)]
Acharya additionally teaches, with regards to claim 18. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame is based on establishing correspondence of features between frames of a video sequence. [(Acharya para 61-62)]
Khan in view of Acharya additionally teaches, with regards to claim 19. see analysis of claim 1 and Khan para 42 Acharya para 104-105
Khan in view of Acharya additionally teaches, with regards to claim 20. see analysis of claim 1 and Khan para 42 Acharya para 104-105
Claims 6 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Khan in view of Acharya in view of Sawhney.
Regarding Claim 6. Khan in view of Acharya does not explicitly show wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises facilitating registration of images comprising the frame captured by the plurality of cameras by feature correspondence between nearest neighbor cameras.
However, in the same/related field of endeavor, Sawhney teaches wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises facilitating registration of images comprising the frame captured by the plurality of cameras by feature correspondence between nearest neighbor cameras. [(para 8, 44 and 32)]
Therefore, in light of above discussion it would have been obvious to one of the ordinary skill in the art, before the effective filing date of the claimed invention, to combine the teaching of the prior arts to improve pose estimation
Sawhney additionally teaches, with regards to claim 11. The method of claim 1, wherein generating at least the partial three-dimensional reconstruction of the scene for the frame comprises minimizing a cost function subject to one or more constraints [(error is minimized {para 44, 55, 61}. Error is a cost function. Also see para 12, 32, 36, 42 )]
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Shahan Rahaman whose telephone number is (571)270-1438. The examiner can normally be reached on 7am - 3:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nasser Goodarzi can be reached at telephone number (571) 272-4195. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
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/SHAHAN UR RAHAMAN/Primary Examiner, Art Unit 2426
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