- Research Article
- Open Access
View Influence Analysis and Optimization for Multiview Face Recognition
EURASIP Journal on Image and Video Processing volume 2007, Article number: 025409 (2007)
We present a novel method to recognize a multiview face (i.e., to recognize a face under different views) through optimization of multiple single-view face recognitions. Many current face descriptors show quite satisfactory results to recognize identity of people with given limited view (especially for the frontal view), but the full view of the human head has not yet been recognizable with commercially acceptable accuracy. As there are various single-view recognition techniques already developed for very high success rate, for instance, MPEG-7 advanced face recognizer, we propose a new paradigm to facilitate multiview face recognition, not through a multiview face recognizer, but through multiple single-view recognizers. To retrieve faces in any view from a registered descriptor, we need to give corresponding view information to the descriptor. As the descriptor needs to provide any requested view in 3D space, we refer to it as "3D" information that it needs to contain. Our analysis in various angled views checks the extent of each view influence and it provides a way to recognize a face through optimized integration of single view descriptors covering the view plane of horizontal rotation from −90∘ to 90∘ and vertical rotation from −30∘ to 30∘. The resulting face descriptor based on multiple representative views, which is of compact size, shows reasonable face recognition performance on any view. Hence, our face descriptor contains quite enough 3D information of a person's face to help for recognition and eventually for search, retrieval, and browsing of photographs, videos, and 3D-facial model databases.
Samal A, Iyengar PA: Automatic recognition and analysis of human faces and facial expressions: a survey. Pattern Recognition 1992,25(1):65-77. 10.1016/0031-3203(92)90007-6
Li SZ, Zhu L, Zhang ZQ, Blake A, Zhang HJ, Shum H: Statistical learning of multi-view face detection. Proceedings of the 7th European Conference on Computer Vision (ECCV '02), May 2002, Copenhagen, Denmark 4: 67-81.
Li Y, Gong S, Liddell H: Support vector regression and classification based multi-view facedetection and recognition. Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition, March 2000, Grenoble, France 300-305.
Shakhnarovich G, Lee L, Darrell T: Integrated face and gait recognition from multiple views. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '01), December 2001, Kauai, Hawaii, USA 1: 439-446.
Blanz V, Vetter T: Face recognition based on fitting a 3D morphable model. IEEE Transactions on Pattern Analysis and Machine Intelligence 2003,25(9):1063-1074. 10.1109/TPAMI.2003.1227983
Bronstein AM, Bronstein MM, Kimmel R: Expression-invariant 3D face recognition. Proceedings of the 4th International Conference on Audio- and Video-Based Biometric Person Authentication (AVBPA '03), June 2003, Guildford, UK, Lecture Notes in Computer Science 2688: 62-69.
Gavrila DM, Davis LS: 3-D model-based tracking of humans in action: a multi-view approach. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '96), June 1996, San Francisco, Calif, USA 73-80.
Bowyer KW, Chang K, Flynn P: A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Computer Vision and Image Understanding 2006,101(1):1-15. 10.1016/j.cviu.2005.05.005
Yamada A, Cieplinski L: MPEG-7 Visual part of eXperimentation Model Version 17.1. 2003.
Kamei T, Yamada A, Kim H, Hwang W, Kim T-K, Kee SC: CE report on Advanced Face Recognition Descriptor. 2002.
Lee W-S, Sohn K-A: Face recognition using computer-generated database. In Proceedings of Computer Graphics International (CGI '04), June 2004, Crete, Greece. IEEE Computer Society Press; 561-568.
Lee W-S, Sohn K-A: Database construction & recognition for multi-view face. In Proceedings of the 6th IEEE International Conference on Automatic Face and Gesture Recognition (FGR '04), May 2004, Seoul, Korea. IEEE Computer Society Press; 350-355.
Graham DB, Allinson NM: Characterizing virtual eigensignatures for general purpose face recognition. In Face Recognition: From Theory to Applications. Edited by: Wechsler H, Phillips PJ, Bruce V, Fogelman-Soulie F, Huang TS. Springer, Berlin, Germany; 1998:446-456.
Park G, Baek Y, Lee H-K: A ranking algorithm using dynamic clustering for content-based image retrieval. Proceedings of the International Conference Image and Video Retrieval (CIVR '02), July 2002, London, UK, Lecture Notes in Computer Science 2383: 328-337.
About this article
Cite this article
Lee, W., Sohn, K. View Influence Analysis and Optimization for Multiview Face Recognition. J Image Video Proc 2007, 025409 (2007). https://doi.org/10.1155/2007/25409
- Face Recognition
- Human Head
- Angle View
- Single View
- Full View