The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 26, 2016

Filed:

May. 09, 2001
Applicants:

Jean-yves Bouguet, Milpitas, CA (US);

Radek Grzeszczuk, Mountain View, CA (US);

Salih Gokturk, Mountain View, CA (US);

Inventors:

Jean-Yves Bouguet, Milpitas, CA (US);

Radek Grzeszczuk, Mountain View, CA (US);

Salih Gokturk, Mountain View, CA (US);

Assignee:

Intel Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/20 (2006.01); G06T 17/00 (2006.01); H04N 19/597 (2014.01); H04N 13/00 (2006.01); H04N 13/02 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00228 (2013.01); G06T 7/2046 (2013.01); G06T 17/00 (2013.01); H04N 19/597 (2014.11); G06T 2207/10016 (2013.01); G06T 2207/30201 (2013.01); H04N 13/0055 (2013.01); H04N 13/0239 (2013.01); H04N 2013/0081 (2013.01);
Abstract

A method and system using a data-driven model for monocular face tracking are disclosed, which provide a versatile system for tracking three-dimensional (3D) images, e.g., a face, using a single camera. For one method, stereo data based on input image sequences is obtained. A 3D model is built using the obtained stereo data. A monocular image sequence is tracked using the built 3D model. Principal Component Analysis (PCA) can be applied to the stereo data to learn, e.g., possible facial deformations, and to build a data-driven 3D model ('3D face model'). The 3D face model can be used to approximate a generic shape (e.g., facial pose) as a linear combination of shape basis vectors based on the PCA analysis.


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