Laser & Optoelectronics Progress, Volume. 57, Issue 18, 181008(2020)

Head Pose Estimation Algorithm Based on Structured Light Three-Dimensional Reconstruction

Junyu Zhong, Jian Qiu*, Peng Han**, Kaiqing Luo, Li Peng, and Dongmei Liu
Author Affiliations
  • School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, Guangdong 510631, China
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    Head pose estimation is widely used in many fields, mostly based on two-dimensional (2D) images. However, there is little research on the combination of three-dimensional (3D) face reconstruction. The reconstructed head 3D information can provide more effective data information for head pose estimation, and greatly improve the accuracy and accuracy of head pose estimation. Hence, in this paper, a recombination of 3D reconstruction based on structured light and 3D head pose estimation is proposed to reconstruct 3D facial morphology and realize 3D point cloud visualization. At the same time, a 3D head pose estimation algorithm is put forward, which searches the nose tip and nose bridge, establishes the space rectangular coordinate system and the face eigen coordinate system, and uses the vertical symmetry of the face to estimate the Euler angle of the head posture. The results show that the Euler angle of the 3D reconstruction can be measured in the range of -25° to 25°. The average and standard deviations of the absolute errors are both less than 1°. The linear correlation between the value and the true value is 99.8%. Comparing with the head pose estimation based on 2D images, the algorithm in this paper is more accurate and robust.

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    Junyu Zhong, Jian Qiu, Peng Han, Kaiqing Luo, Li Peng, Dongmei Liu. Head Pose Estimation Algorithm Based on Structured Light Three-Dimensional Reconstruction[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181008

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    Paper Information

    Category: Image Processing

    Received: Jan. 6, 2020

    Accepted: Feb. 10, 2020

    Published Online: Sep. 2, 2020

    The Author Email: Qiu Jian (qiuj@scnu.edu.cn), Han Peng (hanp@scnu.edu.cn)

    DOI:10.3788/LOP57.181008

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