IP Library Granted Patent US 10,055,879
Granted Patent B2
US 10,055,879 · App. 15/652,009 · Granted Aug 21, 2018

3D human face reconstruction method, apparatus and server

Inventors: Chengjie Wang (Shenzhen, CN); Jilin Li (Shenzhen, CN); Feiyue Huang (Shenzhen, CN); Lei Zhang (Shenzhen, CN)
Assignee: Tencent Technology (Shenzhen) Company Limited
G06T15/10G06T7/73G06T15/04G06T2207/30201G06T2215/16
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Quick Facts
Patent No.
US 10,055,879
App. No.
15/652,009
Granted
Aug 21, 2018
Kind
B2
Abstract

A 3D human face reconstruction method and apparatus, and a server are provided. In some embodiments, the method includes determining feature points on an acquired 2D human face image; determining posture parameters of a human face according to the feature points, and adjusting a posture of a universal 3D human face model according to the posture parameters; determining points on the universal 3D human face model corresponding to the feature points, and adjusting the corresponding points in a sheltered status to obtain a preliminary 3D human face model; and performing deformation adjusting on the preliminary 3D human face model, and performing texture mapping on the deformed 3D human face model to obtain a final 3D human face.

Claims (51)

1. A three-dimensional (3D) human face reconstruction method, comprising:

obtaining a two-dimensional (2D) human face image for 3D human face reconstruction, and determining feature points on the 2D human face image, wherein the feature points are representative of a human face contour;

determining posture parameters of a human face by using the feature points, and adjusting, based on the posture parameters, a posture of a general 3D human face model obtained in advance;

determining points on the general 3D human face model corresponding to the feature points, and adjusting corresponding points in a blocking state to obtain a preliminary 3D human face model;

performing deformation adjusting on the preliminary 3D human face model to obtain a deformed 3D human face model, so that a positional relationship among the corresponding points on the deformed 3D human face model is consistent with a positional relationship among the feature points on the 2D human face image; and

performing texture mapping on the deformed 3D human face model to obtain a 3D human face,

wherein adjusting the corresponding points in the blocking state to obtain the preliminary 3D human face model comprises:

determining a plane in which the corresponding points in the blocking state are located, the plane being perpendicular to the longitudinal axis of the human face;

determining an intersection track between the plane and the general 3D human face model; and

moving the corresponding points to the outermost end of the intersection track, and

wherein the method is performed by one or more processors.

2. The method according to claim 1 , wherein performing deformation adjusting on the preliminary 3D human face model comprises:

calculating displacements of the corresponding points on the preliminary 3D human face model with respect to the feature points, with reference to a proportional relation among the feature points on the 2D human face image;

constructing an interpolation function, and calculating displacements of other points on the preliminary 3D human face model except the corresponding points based on the interpolation function; and

adjusting the preliminary 3D human face model according to the displacements of the corresponding points and the displacements of the non-corresponding points.

3. The method according to claim 2 , wherein constructing the interpolation function comprises constructing the interpolation function by using the radial basis function.

4. The method according to claim 1 , wherein performing texture mapping on the deformed 3D human face model comprises performing the texture mapping by using a similarity-preserving mesh parameterization method.

5. A three-dimensional (3D) human face reconstruction apparatus, comprising:

one or more processors configured to:

obtain a two-dimensional (2D) human face image for 3D human face reconstruction, and determine feature points on the 2D human face image, wherein the feature points are representative of a human face contour;

determine posture parameters of a human face by using the feature points, and adjust, based on the posture parameters, a posture of a general 3D human face model obtained in advance;

determine points on the general 3D human face model corresponding to the feature points, and adjust corresponding points in a blocking state to obtain a preliminary 3D human face model;

perform deformation adjusting on the preliminary 3D human face model to obtain a deformed 3D human face model, so that a positional relationship among the corresponding points on the deformed 3D human face model is consistent with a positional relationship among the feature points on the 2D human face image; and

perform texture mapping on the deformed 3D human face model to obtain a 3D human face,

wherein the one or more processors are further configured to:

determine a plane in which the corresponding points in the blocking state are located, the plane being perpendicular to the longitudinal axis of the human face;

determine an intersection track between the plane and the general 3D human face model; and

move the corresponding points to the outermost end of the intersection track.

6. The 3D human face reconstruction apparatus according to claim 5 , wherein the one or more processors are further configured to:

calculate displacements of the corresponding points on the preliminary 3D human face model with respect to the feature points, with reference to a proportional relation among the feature points on the 2D human face image;

construct an interpolation function, and calculate displacements of other points on the preliminary 3D human face model except the corresponding points based on the interpolation function; and

adjust the preliminary 3D human face model according to the displacements of the corresponding points and the displacements of the non-corresponding points.

7. The 3D human face reconstruction apparatus according to claim 6 , wherein the interpolation function is constructed by using the radial basis function.

8. The 3D human face reconstruction apparatus according to claim 5 , wherein the texture mapping is performed on the deformed 3D human face model based on similarity-preserving mesh parameterization.

9. A server, comprising a three-dimensional (3D) human face reconstruction apparatus, the 3D human face reconstruction apparatus comprising one or more processors and a memory for storing program instructions that, when executed by the one or more processors, cause the one or more processors to:

obtain a two-dimensional (2D) human face image for 3D human face reconstruction, and determine feature points on the 2D human face image, wherein the feature points are representative of a human face contour;

determine posture parameters of a human face by using the feature points, and adjust, based on the posture parameters, a posture of a general 3D human face model obtained in advance;

determine points on the general 3D human face model corresponding to the feature points, and adjust corresponding points in a blocking state to obtain a preliminary 3D human face model;

perform deformation adjusting on the preliminary 3D human face model to obtain a deformed 3D human face model, so that a positional relationship among the corresponding points on the deformed 3D human face model is consistent with a positional relationship among the feature points on the 2D human face image; and

perform texture mapping on the deformed 3D human face model to obtain a 3D human face,

wherein the program instructions further cause the one or more processors to:

determine a plane in which the corresponding points in the blocking state are located, with the plane being perpendicular to the longitudinal axis of the human face;

determine an intersection track between the plane and the general 3D human face model; and

move the corresponding points to the outermost end of the intersection track.

10. The server according to claim 9 , wherein the program instructions further cause the one or more processors to:

calculate displacements of the corresponding points on the preliminary 3D human face model with respect to the feature points, with reference to a proportional relation among the feature points on the 2D human face image;

construct an interpolation function, and calculate displacements of other points on the preliminary 3D human face model except the corresponding points based on the interpolation function; and

adjust the preliminary 3D human face model according to the displacements of the corresponding points and the displacements of the non-corresponding points.

11. The server according to claim 10 , wherein the interpolation function is constructed by using the radial basis function.

12. The server according to claim 9 , wherein the texture mapping is performed on the deformed 3D human face model based on similarity-preserving mesh parameterization.

13. A non-transitory computer readable storage medium, comprising program instructions which, when executed by a processor of a computing device, configure the processor to execute the 3D human face reconstruction method according to claim 1 .

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 25, 2017
From: WANG, CHENGJIE; LI, JILIN; HUANG, FEIYUE; ZHANG, LEI
To: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Reel/Frame 043094/0856 →
Priority Claims (1)
CN 2015 1 0268521 · May 22, 2015 · national
Continuity (2)
Continuation PCTCN2016081452 · May 9, 2016
Related Publication 20170316598A1 · Nov 2, 2017
Cited By (1)
US 12,249,178