Simultaneous Facial Landmark Detection, Pose and Deformation Estimation Under Facial Occlusion

Yue Wu, Chao Gou, Qiang Ji; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 3471-3480

Abstract


Facial landmark detection, head pose estimation, and facial deformation analysis are typical facial behavior analysis tasks in computer vision. The existing methods usually perform each task independently and sequentially, ignoring their interactions. To tackle this problem, we propose a unified framework for simultaneous facial landmark detection, head pose estimation, and facial deformation analysis, and the proposed model is robust to facial occlusion. Following a cascade procedure augmented with model-based head pose estimation, we iteratively update the facial landmark locations, facial occlusion, head pose and facial deformation until convergence. The experimental results on benchmark databases demonstrate the effectiveness of the proposed method for simultaneous facial landmark detection, head pose and facial deformation estimation, even if the images are under facial occlusion.

Related Material


[pdf]
[bibtex]
@InProceedings{Wu_2017_CVPR,
author = {Wu, Yue and Gou, Chao and Ji, Qiang},
title = {Simultaneous Facial Landmark Detection, Pose and Deformation Estimation Under Facial Occlusion},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}