Automatic multiview face detection and pose estimation from videos based on mixture-of-trees model and optical flow

Huisi WU, Laiqun LI, Jingjing LIU, Youcai ZHU, Ping LI, Zhenkun WEN

Research output: Chapter in Book/Report/Conference proceedingChapters

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of 2016 IEEE International Conference on Signal and Image Processing (ICSIP)
Place of PublicationDanvers, MA
PublisherIEEE
Pages282-286
ISBN (Print)9781509023776, 9781509023769
DOIs
Publication statusPublished - 2016

Citation

Wu, 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.

Keywords

  • Face
  • Videos
  • Pose estimation
  • Face detection
  • Optical imaging
  • Image motion analysis

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