Rapid computer modeling of faces for animation

• US 20040213453A1
• Filed: 05/14/2004
• Published: 10/28/2004
• Est. Priority Date: 03/09/2000
• Status: Active Grant

• Current Assignee: Zhigu Holdings Limited
• Original Assignee: Microsoft Corporation
• Inventors: Zhang, Zhengyou, Liu, Zicheng, Cohen, Michael F., Jacobs, Charles E.
• Granted Patent: US 6,944,320 B2
• Time in Patent Office: Days
• US Class Current: 382/154
• CPC Class Codes: G06T 13/40 of characters, e.g. humans, animals or virtual beings
• CPC Class Codes: G06T 15/205 Image-based rendering
• CPC Class Codes: G06T 17/00 Three dimensional [3D] modelling, e.g. data description of 3D objects
• CPC Class Codes: G06T 17/10 Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
• CPC Class Codes: G06T 17/20 Finite element generation, e.g. wire-frame surface description, tesselation
• CPC Class Codes: G06T 2200/08 involving all processing steps from image acquisition to 3D model generation
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/251 involving models
• CPC Class Codes: G06T 7/55 from multiple images
• CPC Class Codes: G06T 7/579 from motion
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: G06T 9/001 Model-based coding, e.g. wire frame
• CPC Class Codes: G06V 20/64 Three-dimensional objects
• CPC Class Codes: G06V 40/165 using facial parts and geometric relationships
• CPC Class Codes: G06V 40/168 Feature extraction; Face representation
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships
• CPC Class Codes: H04N 19/162 User input
• CPC Class Codes: H04N 19/503 : involving temporal prediction adaptive coding with adaptive selection between spatial and temporal predictive coding H04N19/107; adaptive coding with adaptive selection among a plurality of temporal predictive coding modes H04N19/109

Abstract

Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Claims

1. A method of determining the pose of an object in a given 2D image relative to a 3D model of the object, comprising:

matching points of the object in the given image with corresponding points of a base image, wherein each matched point has a corresponding 3D position in the 3D model, the 3D positions being determined by the poses of the images, wherein the pose of the base image is known; and

calculating the pose of the given image such that projections of 3D positions of matched points of the base image onto the given image coincide approximately with the corresponding matched points of the given image.

2. A method as recited in claim 1 wherein the calculating comprises minimizing differences between the projections of 3D positions of matched points of the base image onto the given image and the corresponding matched points of the given image.

3. A method as recited in claim 1 wherein the calculating comprises:

summing the differences between the projections of 3D positions of matched points of the base image onto the given image and the corresponding matched points of the given image; and

calculating a pose that minimizes the summed differences.

4. A method as recited in claim 1 wherein the matching comprises detecting and matching corners of the images.

7. One or more computer-readable media as recited in claim 1 wherein the matching comprises detecting and matching corners of the images.

5. One or more computer-readable media containing a program that is executable by a computer to determine poses of an object in a succession of 2D images, relative to a 3D model of the object;

the program comprising the following actions, for each 2D image in succession;

matching points of the object in the 2D image with corresponding points of a previous 2D image whose pose is already known, wherein the matched points of the previous image has corresponding 3D positions in the 3D model;

calculating a pose for the 2D image that minimizes differences between the projections of 3D positions of matched points of the previous image onto the given image and the corresponding matched points of the given image.

6. One or more computer-readable media as recited in claim 5 wherein the calculating comprises:

summing the differences between the projections of 3D positions of matched points of the previous image onto the given image and the corresponding matched points of the given image; and

calculating the pose to minimize the summed differences.