Single-image human face posture estimation method based on depth value

A face pose, single image technology, applied in computing, computer parts, instruments, etc., can solve the ill-conditioned pose estimation process, the lack of depth information of face features, and the inability to distinguish between interior and exterior points. question

A face pose, single image technology, applied in computing, computer parts, instruments, etc., can solve the ill-conditioned pose estimation process, the lack of depth information of face features, and the inability to distinguish between interior and exterior points. question

CN106570460AActive Publication Date: 2017-04-19SANMING UNIV
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  • Single-image human face posture estimation method based on depth value
  • Single-image human face posture estimation method based on depth value
  • Single-image human face posture estimation method based on depth value

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Embodiment Construction

[0103] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0104] Please refer to figure 1 , the present invention provides a method for estimating the face pose of a single image based on a depth value, characterized in that it comprises the following steps:

[0105] Step S1: Obtain the face image of the pose to be estimated;

[0106] Step S2: Preprocessing, converting the face image of the pose to be estimated into a grayscale image, normalizing the grayscale value to [0,1], performing denoising and standardization processing, and converting the processed grayscale image The size is unified to 64×64;

[0107] Step S3: For the preprocessed grayscale image, introduce the Affine Transformation Invariant Initialization Principle (ATIIA) to establish an initial model, improve the traditional active shape model (ASM) method, and extract the two-dimensional values ​​of ten facial feature points. The ten face feat...

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Abstract

The invention relates to a single-image human face posture estimation method based on a depth value, and the method comprises the following steps: obtaining a human face with a to-be-estimated posture; converting the human face with a to-be-estimated posture into a gray scale image, and carrying out the noise reduction and standardization processing; introducing an affine transformation invariance initialization principle to build an initial model, improving a conventional active shape model method, and extracting the two-dimensional values of ten human face feature points; solving the depth values of ten human face feature points through the perspective imaging principle through employing an iteration algorithm; estimating a human face posture estimation target function; carrying out the primary estimation of the human face posture through four human face feature points, enabling the primary estimation value to serve as the input value for the least square optimization calculation of a target function, and outputting a human face posture result of secondary estimation; carrying out the further optimization of a least square optimization calculation result through employing an M-estimation algorithm, and outputting a final estimation result. The invention overcomes a pathological problem of posture estimation, and is good in posture estimation precision and robustness.

Description

technical field [0001] The invention relates to a single image human face attitude estimation method based on depth value. Background technique [0002] In recent years, although the development of depth camera technology and the advent of Microsoft Kinect have broken the situation of high prices of depth cameras in the past, and two new depth image databases, ETH Face Pose and Biwi Kinect, have appeared in the field of face pose estimation. In practical applications such as customs, airports, exhibition halls and other public places and public security systems for chasing criminals, it still takes time to collect and update the two-dimensional database to the three-dimensional database. Therefore, at present, multi-pose recognition for a single two-dimensional face image is still the mainstream . At present, the frontal face recognition system has achieved good recognition results, but the effective recognition of multi-pose face images is still not good. According to sta...

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Application Information

Patent Timeline
19 Apr 2017
Publication
CN106570460A
IPC
G06K9/00
CPC
G06V40/171
Inventors
邱丽梅; 吴龙