IP Library Granted Patent US 12,192,679
Granted Patent B2
US 12,192,679 · App. 17/249,469 · Granted Jan 7, 2025

Updating 3D models of persons

Inventors: Ran Oz (Maccabim, IL); Yuval Gronau (Ramat Hasharon, IL); Michael Rabinovich (Tel Aviv, IL); Osnat Goren-Peyser (Tel Aviv, IL); Tal Perl (Los Altos, CA); Erez Posner (Rehovot, IL)
Assignee: TRUEMEETING, LTD
H04N7/157G06F3/013G06N3/04G06N3/045G06T7/11G06T7/70G06T15/04G06T15/20G06T15/205G06T17/20G06T19/20H04N7/144H04N7/147H04N7/152G06T19/00G06T2200/08G06T2207/30201G06T2219/2004
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 12,192,679
App. No.
17/249,469
Granted
Jan 7, 2025
Kind
B2
Abstract

A method for updating a current three dimensional (3D) model of a person, that method may include calculating current locations, within a two-dimensional (2D) space, of current face landmark points of a face of a person within a first image; the calculating is based on the current 3D model, and one or more current acquisition parameters of a 2D camera; wherein the current 3D model of the person is located within a 3D space; calculating second locations, within the 2D space, of second face landmark points of the face of the person within a second image that follows the first image; calculating correspondences between the current locations and the second locations; calculating, based on the correspondences, locations of the second face landmark points within the 3D space; and modifying the current 3D model based on the locations of the second face landmark points within the 3D space.

Claims (45)

1. A method for updating a current three dimensional (3D) model of a person, comprising:

(a) participating, using a computerized system of the person, in a virtual 3D video conference;

(b) calculating current locations, within a two-dimensional (2D) space, of current face landmark points of a face of a person within a first image; the calculating is based on the current 3D model, and one or more current acquisition parameters of a 2D camera; wherein the current 3D model of the person is located within a 3D space;

(c) calculating second locations, within the 2D space, of second face landmark points of the face of the person within a second image that follows the first image;

(d) calculating correspondences between the current locations and the second locations;

(e) calculating, based on the correspondences, locations of the second face landmark points within the 3D space; and

(f) modifying the current 3D model based on the locations of the second face landmark points within the 3D space;

wherein steps (b)-(f) are also executed by the computerized device of the person; wherein step (a) also comprises capturing the first image and the second image by a camera of the computerized device of the person;

wherein the method further comprises:

determining parameters of the current 3D model of the person; wherein the parameters differ from image pixels and there are less than three hundred parameters of the current 3D model;

transmitting the parameters of the current 3D model, without transmitting the current 3D model, from the computerized device of the person to computerized devices of other participants of the virtual 3D video conference; wherein the transmitting comprises reducing latency by directly transmitting the parameters to the computerized devices of other participants without sending the parameters via a central server; and

reconstructing an avatar of the person by the computerized devices of the other participants based on the parameters of the current 3D model;

wherein the transmitting the parameters of the current 3D model is preceded by selecting the parameters of the current 3D model, out of a larger group of parameters of the current 3D model, based on (i) an available bandwidth allocated for transmission and (ii) a contribution of the parameters of the current 3D model to a visual perception of the face of the person; where the available bandwidth is several hundred bits per second.

2. The method according to claim 1 wherein the current face landmark points are edge points of the current face landmarks.

3. The method according to claim 1 wherein the current face landmark points are edge points of the current face landmarks and non-edge points of the current face landmarks.

4. The method according to claim 1 wherein the current 3D model comprises a reference 3D model and a current 3D deformation model, wherein the modifying of the current 3D model comprises modifying the current 3D deformation model without substantially modifying the reference 3D model.

5. The method according to claim 4 , comprising determining an update frequency of the 3D model based on the bandwidth.

6. The method according to claim 1 further comprising allocating bitrate, based on the available bandwidth, for a transmission of audio and for the transmission of the parameters of the current 3D model.

7. The method according to claim 1 wherein step (c) comprises segmentation.

8. The method according to claim 1 wherein the parameters define a shape, an expression and a pose of the person.

9. The method according to claim 1 wherein the user computerized device is a laptop without a graphics processing unit (GPU).

10. The method according to claim 1 , wherein the user computerized device is mobile phone.

11. The method according to claim 1 , wherein the parameters are ordered according to importance of the parameters.

12. The method according to claim 1 , wherein a number of bits per parameter is determined according to the available bandwidth allocated to the transmission.

13. A non-transitory computer readable medium for updating a current three dimensional (3D) model of a person, the non-transitory computer readable medium stores instructions for:

(a) participating, using a computerized system of the person, in a virtual 3D video conference;

(b) calculating current locations, within a two-dimensional (2D) space, of current face landmark points of a face of a person within a first image; the calculating is based on the current 3D model, and one or more current acquisition parameters of a 2D camera; wherein the current 3D model of the person is located within a 3D space;

(c) calculating second locations, within the 2D space, of second face landmark points of the face of the person within a second image that follows the first image;

(d) calculating correspondences between the current locations and the second locations;

(e) calculating, based on the correspondences, locations of the second face landmark points within the 3D space; and

(f) modifying the current 3D model based on the locations of the second face landmark points within the 3D space;

wherein steps (b)-(f) are also executed by the computerized device of the person; wherein step (a) also comprises capturing the first image and the second image by a camera of the computerized device of the person;

wherein the non-transitory computer readable medium further stores instructions for:

determining parameters of the current 3D model of the person; wherein the parameters differ from image pixels and there are less than three hundred parameters of the current 3D model;

transmitting the parameters of the current 3D model, without transmitting the current 3D model, from the computerized device of the person to computerized devices of other participants of the virtual 3D video conference; wherein the transmitting comprises reducing latency by directly transmitting the parameters to the computerized devices of other participants without sending the parameters via a central server; and

reconstructing an avatar of the person by the computerized devices of the other participants based on the parameters of the current 3D model;

wherein the transmitting the parameters of the current 3D model is preceded by selecting the parameters of the current 3D model, out of a larger group of parameters of the current 3D model, based on (i) an available bandwidth allocated for transmission and (ii) a contribution of parameters of the current 3D model to a visual perception of the face of the person; and wherein the available bandwidth is several hundred bandwidths per second.

14. The non-transitory computer readable medium according to claim 13 wherein the current face landmark points are edge points of the current face landmarks.

15. The non-transitory computer readable medium according to claim 13 wherein the current face landmark points are edge points of the current face landmarks and non-edge points of the current face landmarks.

16. The non-transitory computer readable medium according to claim 13 wherein the current 3D model comprises a reference 3D model and a current 3D deformation model, wherein the modifying of the current 3D model comprises modifying the current 3D deformation model without substantially modifying the reference 3D model.

17. The non-transitory computer readable medium according to claim 16 , comprising determining an update frequency of the 3D model based on the bandwidth.

18. The non-transitory computer readable medium according to claim 13 that stores instructions for allocating bitrate, based on the available bandwidth, for a transmission of audio and for the transmission of the parameters of the current 3D model.

19. The non-transitory computer readable medium according to claim 13 wherein step (b) comprises segmentation.

20. The non-transitory computer readable medium according to claim 13 wherein the parameters define a shape, an expression and a pose of the person.

21. The non-transitory computer readable medium according to claim 13 , wherein the user computerized device is a laptop without a graphics processing unit (GPU).

Assignments (4)
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE'S NAME PREVIOUSLY RECORDED AT REEL: 60665 FRAME: 246. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT . Recorded Sep 4, 2024
From: OZ, RAN; GRONAU, YUVAL; RABINOVICH, MICHAEL; GOREN-PEYSER, OSNAT; PERL, TAL
To: TRUEMEETING, LTD
Reel/Frame 068847/0786 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE PREVIOUSLY RECORDED ON REEL 60665 FRAME 246. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 18, 2024
From: OZ, RAN; GRONAU, YUVAL; RABINOVICH, MICHAEL; GOREN-PEYSER, OSNAT; PERL, TAL
To: TRUEMEETING, LTD
Reel/Frame 068685/0922 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 25, 2022
From: POSNER, EREZ
To: TRUE MEETING INC.
Reel/Frame 061534/0424 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 29, 2022
From: OZ, RAN; GRONAU, YUVAL; RABINOVICH, MICHAEL; GOREN-PEYSER, OSNAT; PERL, TAL
To: TRUE MEETING INC.
Reel/Frame 060665/0246 →
Continuity (4)
Provisional Application 63199014 · Dec 1, 2020
Provisional Application 63081860 · Sep 22, 2020
Provisional Application 63023836 · May 12, 2020
Related Publication 20210358227A1 · Nov 18, 2021
References Cited (49)
US 6549200B1 · Mortlock · 2003 [cited by applicant]
US 7139767B1 · Taylor · 2006 [cited by examiner]
US 8666119B1 · Mallet · 2014 [cited by examiner]
US 9424678B1 · Enakiev · 2016 [cited by applicant]
US 10652565B1 · Zhang · 2020 [cited by applicant]
US 10841537B2 · Valli · 2020 [cited by applicant]
US 11070768B1 · Krol · 2021 [cited by applicant]
US 11076128B1 · Krol · 2021 [cited by applicant]
US 11095857B1 · Krol · 2021 [cited by applicant]
US 20030068098A1 · Rondinelli · 2003 [cited by applicant]
US 20040104935A1 · Williamson · 2004 [cited by applicant]
US 20050179695A1 · Saito · 2005 [cited by applicant]
US 20060066717A1 · Miceli · 2006 [cited by applicant]
US 20070014485A1 · McAlpine · 2007 [cited by examiner]
US 20100253495A1 · Asano · 2010 [cited by applicant]
US 20110296324A1 · Goossens · 2011 [cited by applicant]
US 20140043329A1 · Wang · 2014 [cited by examiner]
US 20140160239A1 · Tian · 2014 [cited by applicant]
US 20140204084A1 · Corazza · 2014 [cited by applicant]
US 20140266774A1 · Greene · 2014 [cited by examiner]
US 20150215351A1 · Barzuza et al. · 2015 [cited by applicant]
US 20150381939A1 · Cunico · 2015 [cited by applicant]
US 20160234475A1 · Courchesne et al. · 2016 [cited by applicant]
US 20160316170A1 · Smith · 2016 [cited by applicant]
US 20170243387A1 · Li · 2017 [cited by applicant]
US 20170339372A1 · Valli · 2017 [cited by applicant]
US 20180027307A1 · Ni · 2018 [cited by applicant]
US 20180035079A1 · Hui · 2018 [cited by applicant]
US 20180144535A1 · Ford · 2018 [cited by applicant]
US 20180302610A1 · Masuda · 2018 [cited by applicant]
US 20180321738A1 · Jassal · 2018 [cited by applicant]
US 20190025587A1 · Osterhout et al. · 2019 [cited by applicant]
US 20190124316A1 · Yoshimura · 2019 [cited by applicant]
US 20190130629A1 · Chand · 2019 [cited by applicant]
US 20190188895A1 · Miller, IV et al. · 2019 [cited by applicant]
US 20190219700A1 · Coombe · 2019 [cited by applicant]
US 20190253667A1 · Valli · 2019 [cited by applicant]
US 20190384404A1 · Raghoebardajal · 2019 [cited by applicant]
US 20200051304A1 · Choi · 2020 [cited by applicant]
US 20200184721A1 · Ge · 2020 [cited by applicant]
US 20200273247A1 · Lim · 2020 [cited by applicant]
US 20200357158A1 · Zhang · 2020 [cited by examiner]
US 20210035307A1 · Shih · 2021 [cited by applicant]
US 20210052138A1 · Bevis · 2021 [cited by applicant]
US 20210104063A1 · Kassis · 2021 [cited by applicant]
US 20210149189A1 · Hux · 2021 [cited by applicant]
Zhang M, Haung L, Zhu M. Occluded face restoration based on Generative Adversarial Networks. In2020 3rd International Confrence on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Apr. 24, 2020… [cited by applicant]
Roberts, David, et al. “Communicating eye-gaze across a distance: Comparing an eye-gaze enabled immersive collaborative virtual environment, aligned video conferencing, and being together.” 2009 IEEE Virtual Reality Con… [cited by applicant]
Arrington Research, “ViewPoint EyeTracker”, published 2010. [cited by applicant]