IP Library Granted Patent US 12,340,590
Granted Patent B2
US 12,340,590 · App. 18/746,575 · Granted Jun 24, 2025

Method and apparatus for a wearable computer

Inventor: Masoud Vaziri (Richardson, TX)
Assignee: OPTICS INNOVATION LLC
G06V20/52G02B13/16G02B26/0875G02B27/0093G02B27/017G02B27/0172G02B27/64G06F1/163G06F3/012G06F3/013G06F3/015G06F3/017G06F3/0484G06F3/04842G06F3/167G06V20/597G06V40/19H04N7/185H04N23/11H04N23/56H04N23/58H04R1/028H04W4/023G02B2027/0132G02B2027/0138G02B2027/014G02B2027/0178G02B2027/0187G06F2203/04806H04R2201/107H04R2460/13
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,340,590
App. No.
18/746,575
Granted
Jun 24, 2025
Kind
B2
Abstract

An imaging apparatus includes a display device and a camera configured to generate image data reproducible as a series of images of a scene. Each of the series of images has a maximum field of view. A processor is configured to receive the image data, display at least a portion of the series of images, analyze the image data to determine if an object is recognized in each of the series of images, and generate a history of the series of images. The history is indicative of whether each of the series of images includes the object. Based at least in part on the history, the processor is configured to cause the display of the at least a portion of the series of images to be modified to: zoom in on the object, pan within the maximum field of view, zoom out on the scene, or any combination thereof.

Claims (42)

1. An imaging apparatus comprising:

a camera configured to generate image data that is reproducible as a series of images of a scene, each of the series of images of the scene having a maximum field of view dictated by the camera;

a display device; and

a processor configured to:

receive the image data from the camera;

display at least a portion of the series of images of the scene on the display device;

analyze the image data to determine if an object is recognized in each of the series of images of the scene;

generate a history of the series of images of the scene, the history being indicative of whether each of the series of images of the scene includes the object; and

based at least in part on the history of the series of images, cause the display of the at least a portion of the series of images of the scene to be modified to:

(i) zoom in on the object,

(ii) pan within the maximum field of view,

(iii) zoom out on the scene, or

(iv) any combination of (i), (ii), and (iii).

2. The imaging apparatus of claim 1 , wherein the panning within the maximum field of view follows the object.

3. The imaging apparatus of claim 1 , wherein the processor is configured to zoom in, pan, or zoom out automatically without additional input.

4. The imaging apparatus of claim 1 , responsive to the history of the series of images spanning a predetermined number of consecutive images in which the object is recognized, the processor is configured to cause the display of the at least a portion of the series of images of the scene to zoom in on the object such that the display of the at least a portion of the series of images of the scene includes a zoomed field of view that is less than the maximum field of view.

5. The imaging apparatus of claim 4 , responsive to the history of the series of images spanning the predetermined number of consecutive images in which the object is recognized, the processor is further configured to cause the display of the at least a portion of the series of images of the scene to pan within the maximum field of view such that the display of the at least a portion of the series of images of the scene is centered on the object.

6. The imaging apparatus of claim 4 , wherein the predetermined number of consecutive images spans a time period of at least 0.5 seconds.

7. The imaging apparatus of claim 1 , responsive to the history of the series of images spanning a predetermined number of consecutive images in which the object is not recognized, the processor is configured to cause the display of the at least a portion of the series of images of the scene to zoom out on the scene such that the display of the at least a portion of the series of images of the scene includes the maximum field of view.

8. The imaging apparatus of claim 7 , wherein the predetermined number of consecutive images spans a time period of at least 0.5 seconds.

9. The imaging apparatus of claim 1 , wherein the image data is reproducible as a video image of the scene and each of the series of images of the scene is a frame in the video image of the scene.

10. The imaging apparatus of claim 1 , wherein the object is a person or a portion of a person.

11. An imaging method comprising:

generating, via a camera, image data that is reproducible as a series of images of a scene, each of the series of images of the scene having a maximum field of view dictated by the camera;

receiving, via a processor, the image data from the camera;

displaying, via the processor, on a display device at least a portion of the series of images of the scene;

analyzing, via the processor, the image data to determine if an object is recognized in each of the series of images of the scene;

generating, via the processor, a history of the series of images of the scene, the history being indicative of whether each of the series of images of the scene includes the object; and

causing, via the processor and based at least in part on the history of the series of images, the display of the at least a portion of the series of images of the scene to be modified by:

(i) zooming in on the object,

(ii) panning within the maximum field of view,

(iii) zooming out on the scene, or

(iv) any combination of (i), (ii), and (iii).

12. The imaging method of claim 11 , wherein the panning within the maximum field of view follows the object.

13. The imaging method of claim 11 , wherein the zooming in, panning, or zooming out is executed automatically without additional input.

14. The imaging method of claim 11 , wherein responsive to the history of the series of images spanning a predetermined number of consecutive images in which the object is recognized, the display of the at least a portion of the series of images of the scene is modified by zooming in on the object such that the display of the at least a portion of the series of images of the scene includes a zoomed field of view that is less than the maximum field of view.

15. The imaging method of claim 14 , wherein responsive to the history of the series of images spanning the predetermined number of consecutive images in which the object is recognized, the display of the at least a portion of the series of images of the scene is modified by panning within the maximum field of view such that the display of the at least a portion of the series of images of the scene is centered on the object.

16. The imaging method of claim 14 , wherein the predetermined number of consecutive images spans a time period of at least 0.5 seconds.

17. The imaging method of claim 11 , wherein responsive to the history of the series of images spanning a predetermined number of consecutive images in which the object is not recognized, the display of the at least a portion of the series of images of the scene is modified by zooming out on the scene such that the display of the at least a portion of the series of images of the scene includes the maximum field of view.

18. The imaging method of claim 17 , wherein the predetermined number of consecutive images spans a time period of at least 0.5 seconds.

19. The imaging method of claim 11 , wherein the image data is reproducible as a video image of the scene and each of the series of images of the scene is a frame in the video image of the scene.

20. The imaging method of claim 1 , wherein the object is a person or a portion of a person.

Assignments (6)
NUNC PRO TUNC ASSIGNMENT Recorded Oct 18, 2024
From: VAZIRI, MASOUD
To: U & LIFE CORPORATION
Reel/Frame 068941/0770 →
MERGER AND CHANGE OF NAME Recorded Oct 18, 2024
From: U & LIFE CORPORATION; I2I, INC.
To: I2I, INC.
Reel/Frame 068941/0950 →
MERGER AND CHANGE OF NAME Recorded Oct 18, 2024
From: U & LIFE CORPORATION; I2I, INC.
To: I2I, INC.
Reel/Frame 068942/0062 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 18, 2024
From: IPAL INC.
To: VAZIRI, MOJTABA
Reel/Frame 068942/0281 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 18, 2024
From: VAZIRI, MOJTABA
To: OPTICS INNOVATION LLC
Reel/Frame 068942/0347 →
CHANGE OF NAME Recorded Oct 18, 2024
From: I2I, INC.
To: IPAL INC.
Reel/Frame 069206/0819 →
Continuity (15)
Continuation 17887439 · Aug 13, 2022
Continuation 16578285 · Sep 21, 2019
Continuation 15859526 · Dec 31, 2017
Continuation 15663753 · Jul 30, 2017
Continuation 14985398 · Dec 31, 2015
Continuation In Part 13175421 · Jul 1, 2011
Continuation In Part 12794283 · Jun 4, 2010
Provisional Application 62205783 · Aug 17, 2015
Provisional Application 62128537 · Mar 5, 2015
Provisional Application 62099128 · Dec 31, 2014
Provisional Application 61471397 · Apr 4, 2011
Provisional Application 61471376 · Apr 4, 2011
Provisional Application 61369618 · Jul 30, 2010
Provisional Application 61184232 · Jun 4, 2009
Related Publication 20240420477A1 · Dec 19, 2024
References Cited (167)
US 4028725A · Lewis · 1977 [cited by applicant]
US 4907296A · Blecha · 1990 [cited by applicant]
US 5262871A · Wilder · 1993 [cited by applicant]
US 5856811A · Shih · 1999 [cited by applicant]
US 5859921A · Suzuki · 1999 [cited by applicant]
US 6107618A · Fossum · 2000 [cited by examiner]
US 6163336A · Richards · 2000 [cited by applicant]
US 6198485B1 · Mack · 2001 [cited by applicant]
US 6307526B1 · Mann · 2001 [cited by applicant]
US 6434280B1 · Peleg · 2002 [cited by applicant]
US 6486799B1 · Still · 2002 [cited by applicant]
US 6661495B1 · Popovich · 2003 [cited by applicant]
US 6766067B2 · Freeman · 2004 [cited by applicant]
US 6850629B2 · Jeon · 2005 [cited by applicant]
US 7023464B1 · Harada · 2006 [cited by applicant]
US 7331671B2 · Hammond · 2008 [cited by applicant]
US 7391887B2 · Durnell · 2008 [cited by applicant]
US 7492926B2 · Kang · 2009 [cited by applicant]
US 7538326B2 · Johnson · 2009 [cited by examiner]
US 7629582B2 · Hoffman · 2009 [cited by examiner]
US 7697024B2 · Currivan · 2010 [cited by applicant]
US 7715658B2 · Cho · 2010 [cited by applicant]
US 7894666B2 · Mitarai · 2011 [cited by applicant]
US 7915652B2 · Lee · 2011 [cited by examiner]
US 8014632B2 · Matsumoto · 2011 [cited by applicant]
US 8045764B2 · Hamza · 2011 [cited by examiner]
US 8139089B2 · Doyle · 2012 [cited by applicant]
US 8159519B2 · Kurtz · 2012 [cited by applicant]
US 8305899B2 · Luo · 2012 [cited by applicant]
US 8432492B2 · Deigmoeller · 2013 [cited by applicant]
US 8520970B2 · Strandemar · 2013 [cited by examiner]
US 8872910B1 · Vaziri · 2014 [cited by applicant]
US 9230140B1 · Ackley · 2016 [cited by applicant]
US 9438491B1 · Van Broeck · 2016 [cited by applicant]
US 9438819B2 · Van Broeck · 2016 [cited by applicant]
US 9618746B2 · Browne · 2017 [cited by applicant]
US 9674490B2 · Koravadi · 2017 [cited by applicant]
US 9779311B2 · Lee · 2017 [cited by applicant]
US 9727790B1 · Vaziri · 2017 [cited by applicant]
US 9858676B2 · Bostick · 2018 [cited by applicant]
US 9864372B2 · Chen · 2018 [cited by applicant]
US 10039445B1 · Torch · 2018 [cited by applicant]
US 10064552B1 · Vaziri · 2018 [cited by applicant]
US 10152811B2 · Johnson · 2018 [cited by examiner]
US 10374109B2 · Mazur · 2019 [cited by examiner]
US 10708514B2 · Haltmaier · 2020 [cited by applicant]
US 10850693B1 · Pertsel · 2020 [cited by examiner]
US 11189017B1 · Bagai · 2021 [cited by applicant]
US 11287262B2 · Dooley · 2022 [cited by applicant]
US 11450113B1 · Vaziri · 2022 [cited by examiner]
US 11873751B2 · Byrne · 2024 [cited by examiner]
US 20030122930A1 · Schofield · 2003 [cited by applicant]
US 20040212882A1 · Liang · 2004 [cited by applicant]
US 20040218834A1 · Bishop · 2004 [cited by applicant]
US 20060033936A1 · Lee · 2006 [cited by examiner]
US 20060033992A1 · Solomon · 2006 [cited by applicant]
US 20070041663A1 · Cho · 2007 [cited by applicant]
US 20070115349A1 · Currivan · 2007 [cited by applicant]
US 20080010060A1 · Asano · 2008 [cited by applicant]
US 20080030592A1 · Border · 2008 [cited by applicant]
US 20080036875A1 · Jones · 2008 [cited by applicant]
US 20080198324A1 · Fuziak · 2008 [cited by applicant]
US 20080291295A1 · Kato · 2008 [cited by applicant]
US 20080297589A1 · Kurtz · 2008 [cited by applicant]
US 20090189974A1 · Deering · 2009 [cited by applicant]
US 20090273675A1 · Jonsson · 2009 [cited by examiner]
US 20090302219A1 · Johnson · 2009 [cited by examiner]
US 20100053555A1 · Enriquez · 2010 [cited by applicant]
US 20100103276A1 · Border · 2010 [cited by applicant]
US 20100128135A1 · Filipovich · 2010 [cited by applicant]
US 20100157078A1 · Atanassov · 2010 [cited by applicant]
US 20100157079A1 · Atanassov · 2010 [cited by applicant]
US 20100208207A1 · Connell, II · 2010 [cited by applicant]
US 20100240988A1 · Varga · 2010 [cited by applicant]
US 20100254630A1 · Ali · 2010 [cited by applicant]
US 20100277619A1 · Scarff · 2010 [cited by applicant]
US 20100289941A1 · Ito · 2010 [cited by applicant]
US 20100290668A1 · Friedman · 2010 [cited by applicant]
US 20100290685A1 · Wein · 2010 [cited by applicant]
US 20110144462A1 · Lifsitz · 2011 [cited by examiner]
US 20110263946A1 · El Kaliouby · 2011 [cited by applicant]
US 20110279666A1 · Stromborn · 2011 [cited by applicant]
US 20120257005A1 · Browne · 2012 [cited by applicant]
US 20130106911A1 · Salsman · 2013 [cited by applicant]
US 20130121525A1 · Chen · 2013 [cited by applicant]
US 20130242057A1 · Hong · 2013 [cited by applicant]
US 20140146153A1 · Birnkrant · 2014 [cited by applicant]
US 20140267757A1 · Abramson · 2014 [cited by examiner]
US 20140267890A1 · Lelescu · 2014 [cited by applicant]
US 20140313335A1 · Koravadi · 2014 [cited by applicant]
US 20150009550A1 · Misago · 2015 [cited by applicant]
US 20150209002A1 · De Beni · 2015 [cited by applicant]
US 20160012280A1 · Ito · 2016 [cited by applicant]
US 20160179093A1 · Prokorov · 2016 [cited by applicant]
US 20160225192A1 · Jones · 2016 [cited by applicant]
US 20170007351A1 · Yu · 2017 [cited by applicant]
US 20170019599A1 · Muramatsu · 2017 [cited by applicant]
US 20170099479A1 · Browd · 2017 [cited by applicant]
US 20170142312A1 · Dal Mutto · 2017 [cited by applicant]
US 20170181802A1 · Sachs · 2017 [cited by applicant]
US 20170225336A1 · Deyle · 2017 [cited by applicant]
US 20170322410A1 · Watson · 2017 [cited by applicant]
US 20170360578A1 · Shin · 2017 [cited by applicant]
US 20180012413A1 · Jones · 2018 [cited by applicant]
US 20180096468A1 · Nguyen · 2018 [cited by examiner]
US 20180188892A1 · Levac · 2018 [cited by applicant]
US 20180330473A1 · Foi · 2018 [cited by applicant]
US 20190101644A1 · DeMersseman · 2019 [cited by examiner]
US 20190141236A1 · Bergstrom · 2019 [cited by examiner]
US 20190175214A1 · Wood · 2019 [cited by applicant]
US 20190254754A1 · Johnson · 2019 [cited by applicant]
US 20190272336A1 · Ciecko · 2019 [cited by applicant]
US 20200041261A1 · Bernstein · 2020 [cited by applicant]
US 20200077033A1 · Chan · 2020 [cited by applicant]
US 20200117025A1 · Sauer · 2020 [cited by applicant]
US 20200141807A1 · Poirier · 2020 [cited by examiner]
US 20200242421A1 · Sobhany · 2020 [cited by examiner]
US 20200330179A1 · Ton · 2020 [cited by applicant]
US 20210067764A1 · Shau · 2021 [cited by applicant]
US 20210136171A1 · Badam · 2021 [cited by examiner]
US 20210291739A1 · Kasarla · 2021 [cited by examiner]
“A High Speed Eye Tracking System with Robust Pupil Center Estimation Algorithm”, Proceedings of the 29th Ammal International Conference of the IEEE EMBS, 25 Kyon, France, pp. 3331-3334, Aug. 2007. [cited by applicant]
“A Novel Method of Video-Based Pupil Tracking”, Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics, San Antonio, Tex., USA—pp. 1255-1262, Oct. 2009. [cited by applicant]
Athanasios Papoulis; A New Algorithm in Spectral Analysis and Band-Limited Extrapolation; IEEE Transactions on Circuits and Systems, Sep. 1975; vol. CAS-22, No. 9; pp. 735-742. [cited by applicant]
A Zandifar, R. Duraiswami, L.S. Davis, A video-based framework for the analysis of presentations/posters, 2003 (Year: 2003) 10 pages. [cited by applicant]
Barbara Zitova et al.; Image Registration Methods: a Survey; Department of Image Processing; Institute of Information Theory and Automation Academy of Sciences of the Szech Republic; Image and Vision Computing; pp. 977-… [cited by applicant]
B. K. Gunturk, “Super-resolution imaging”, in Compu-tational Photography Methods and Applications, by R. Lukac, CRC Press, 2010 [Abstract Provided]. [cited by applicant]
Cheng et al. Developing a Real-Time Identify-and-Locate System for the Blind. Workshop on Computer Vision Applications for the Visually Impaired, James Coughlan and Roberto Manduchi, Oct. 2008, Marseille, France. [cited by applicant]
Danny Keren et al.; Image Sequence Enhancement Using Sub-pixel Displacements; Department of computer science; The Hebrew University of Jerusalem; 1988 IEEE; pp. 742-746. [cited by applicant]
D. Li, D. Winfield and D. Parkhurst, “Starburst: A Hybrid algorithm for video based eye tracking combining feature-based and model-based approaches”, Iowa State Univer-sity, Ames, Iowa. [cited by applicant]
Edward R. Dowski, Jr. et al.; Extended Depth of Field Through Wave-Front Coding; Apr. 10, 1995; Optical Society of America; vol. 34, No. 11; Applied Optics pp. 1859-1866. [cited by applicant]
Eran Gur and Zeev Zalevsky; Single-Image Digital Super-Resolution a Revised Gerchberg-Papoulis Algorithm; AENG International Journal of Computer Science; Nov. 17, 2007; pp. 1-5. [cited by applicant]
Extrema.m, http:/lwww.mathworks.com/matlabcentral/fileexchange/12275-extrema-m-extrema2-m, Sep. 14, 2006. [cited by applicant]
Eyelink User Manual, SR Research Lid., Copyright 2005-2008, 134 pages. [cited by applicant]
Eyelink Data Viewer User's Manual, SR Research Lid., Copyright 2002-2008, 149 pages. [cited by applicant]
Fritz Gleyo, Microsoft May Make Life-Sized Cortana in Person for HoloLens, (Dec. 14, 2015). [cited by applicant]
Guestrin et al. “General Theory of Remote Gaze Estimation Using the Pupil Center and Corneal Reflections”, IEEE Trans. Biomedical Eng., vol. 53, No. 6, pp. 1124-1133, (Jun. 2006). [cited by applicant]
Jessi Hempel, Project HoloLens: Our Exclusive Hands-On With Microsoft's Holographic Goggles, (Jan. 21, 2015). [cited by applicant]
John Bardsley et al.; Blind Iterative Restoration of Images With Spatially-Varying Blur; 9 pages. [cited by applicant]
J. Goodman, Introduction to Fourier Optics, 2nd edition, 160-165, McGraw-Hill, 1988. [cited by applicant]
Jordan Novet, Microsoft could build a life-sized Cortana for HoloLens, https://www.technologyrecord.com/Article/introducing-microsoft-hololens-development-edition-48296. [cited by applicant]
Kennet Kubala et al.; Reducing Complexity in Computational Imaging Systems; CDM Optics, Inc.; Sep. 8, J003; vol. 11, No. 18; Optics Express; pp. 2102-2108. [cited by applicant]
Lees et al. (Ultrasound Imaging in Three and Four Dimensions, Seminars in Ultrasound, CT, and MR/, vol. 22, No. 1 (Feb. 2001): pp. 85-105, (Year: 2001). [cited by applicant]
Lindsay James, Introducing Microsoft HoloLens Development Edition, https://blogs.windows.com/ :levices/2015/04/30/build-2015-a-closer-look-at-the-microsoft-hololens-hardware/. [cited by applicant]
Lisa Gottesfeld Brown; A Survey of Image Registration Techniques; Department of Computer Science; Columbia University; Jan. 12, 1992; pp. 1-60. [cited by applicant]
Malcolm et al. Combining topdown processes to guide eye movements during real-world scene search. Journal of Vision, 10(2):4, p. 1-11 (2010). [cited by applicant]
Maria E. Angelopoulou et al.; FPGA-based Real-lime Super-Resolution on an Adaptive Image Sensor; Department of Electrical and Electronic Engineering, Imperial College London; 9 pages. [cited by applicant]
Maria E. Angelopoulou et al.; Robust Real-Time Super-Resolution on FPGA and an Application to Video Enhancement; Imperial College London; ACM Journal Name; Sep. 2008; vol. V, No. N; pp. 1-27. [cited by applicant]
Moreno et al. Classification of visual and linguistic tasks using eye-movement features; Journal of Vision (2014) 14(3):11, 1-18. [cited by applicant]
Oliver Bowen et al.; Real-Time Image Super Resolution Using an FPGA; Department of Electrical and Electronic Engineering; Imperial College London; 2008 IEEE; pp. 89-94. [cited by applicant]
Patrick Vandewalle et al.; A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution; Ecole Polytechnique Federal de Lausanne, School of Computer and Communication Sciences; Depa… [cited by applicant]
P. C. Hansen, J. G. Nagy, D. P. O'Leary, Deblurring Images: matrices, Spectra and Filtering, SIAM (2006) [Abstract Provided]. [cited by applicant]
P. Milanfar, Super-Resolution Imaging, CRC Press (2011) [Abstract Provided]. [cited by applicant]
Pravin Bhat et al.; Using Photographs to Enhance Videos of a Static Scene; University of Washington; Microsoft Research; Adobe Systems; University of California; The Eurographics Association 2007; pp. 1-12. [cited by applicant]
R. W. Gerchberg, “Super-resolution through error energy reduction”, Optica Acta, vol. 21, No. 9, pp. 709-720,(1974). [cited by applicant]
S. Chaudhuri, Super-Resolution Imaging, Kluwer Aca-demic Publishers (2001) [Abstract Provided]. [cited by applicant]
Sang-Hyuck Lee et al.; Breaking Diffraction Limit of a Small F-Number Compact Camera Using Wavefront Coding; Center for Information Storage Device; Department of Mechanical Engineering, Yonsei University, Shinchondong, … [cited by applicant]
Sawhney, H. et al.; “Hybrid Stereo Camera: An IBR Approach for Synthesis of Very High Resolution Stereoscopic Image Sequences”; AC SIGGRAPH, pp. 451-460; 2001 (10 pages). [cited by applicant]
Suk Hwan Lim and Amnon Silverstein; Estimation and Removal of Motion Blur by Capturing Two Images With Different Exposures; HP Laboratories and NVidia Corp.; HPL-2008-170; Oct. 21, 2008; 8 pages. [cited by applicant]
S.-W Jung and S.-J. Ko, “Image deblurring using multi-exposed images” in Computational Photography 65 Methods and Applications, by R. Lukac, CRC Press, 2010. [Abstract Provided]. [cited by applicant]
Todd Holmdahl, BUILD 2015: A closer look at the Microsoft HoloLens hardware, https://blogs.windows.com/ :levices/2015/04/30/build-2015-a-closer-look-at-the-microsoft-hololens-hardware/. [cited by applicant]
Tod R. Lauer; Deconvolution With a Spatially-Variant PSF; National Optical Astronomy Observatory; Tucson, AZ; arXiv:astro-ph/0208247v1; Aug. 12, 2002; 7 pages. [cited by applicant]
V. Barmore, Iterative-Interpolation Super-Resolution Image Reconstruction, Springer (2009) [Abstract Provided]. [cited by applicant]
W. Thomas Cathey et al.; New Paradigm for Imaging Systems; Optical Society of America; Applied Optics; Oct. 10, 2002; vol. 41, No. 29; pp. 6080-6092. [cited by applicant]
William T. Freeman et al.; Example-Based Super-Resolution; Mitsubishi Electric Research Labs; Mar./Apr. J002; IEEE Computer Graphics and Applications; pp. 56-65. [cited by applicant]
Zitnick, L. et al.; “Stereo for Image-Based Rendering Using Image Over-Segmentation”; International Journal of Computer Visions; 2006 (32 pages). [cited by applicant]
Z. Zalevsky, D. Mendlovic, Optical Superresolution, 2004 (Year: 2004) 261 pages. [cited by applicant]
Cited By (1)
US 12,549,841