Face detection is an important task in the field of computer vision, which is widely used in the field of security, human-machine interaction, identity recognition, and etc. Many existing methods are developed for image based face pose estimation, but few of them can be directly extended to videos. However, video-based face pose estimation is much more important and frequently used in real applications. This paper describes a method of automatic face pose estimation from videos based on mixture-of-trees model and optical flow. Unlike the traditional mixture-of-trees model, which may easily incur errors in losing faces or with wrong angles for a sequence of faces in video, our method is much more robust by considering the spatio-temporal consistency on the face pose estimation for video. To preserve the spatio-temporal consistency from one frame to the next, this method employs an optical flow on the video to guide the face pose estimation based on mixture-of-trees. Our method is extensively evaluated on videos including different faces and with different pose angles. Both visual and statistics results demonstrated its effectiveness on automatic face pose estimation. Copyright © 2016 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
|Title of host publication||Proceedings of 2016 IEEE International Conference on Signal and Image Processing (ICSIP)|
|Place of Publication||Danvers, MA|
|ISBN (Print)||9781509023776, 9781509023769|
|Publication status||Published - 2016|
CitationWu, H., Li, L., Liu, J., Zhu, Y., Li, P., & Wen, Z. (2016). Automatic multiview face detection and pose estimation from videos based on mixture-of-trees model and optical flow. In Proceedings of 2016 IEEE International Conference on Signal and Image Processing (ICSIP) (pp. 282-286). Danvers, MA: IEEE.
- Pose estimation
- Face detection
- Optical imaging
- Image motion analysis