Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Recognition from Long-Term Observations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Comparative Evaluation of Face Sequence Matching for Content-Based Video Access
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Streaming Face Recognition Using Multicamera Video Arrays
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Video-Based Online Face Recognition Using Identity Surfaces
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
A System Identification Approach for Video-based Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Face Recognition from Face Motion Manifolds using Robust Kernel Resistor-Average Distance
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
Face Verification using External Features
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A pose-wise linear illumination manifold model for face recognition using video
Computer Vision and Image Understanding
Person recognition using facial video information: A state of the art
Journal of Visual Languages and Computing
Visual tracking and recognition using probabilistic appearance manifolds
Computer Vision and Image Understanding
Video face recognition with graph-based semi-supervised learning
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Patch-based face recognition from video
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Video-based face recognition using probabilistic appearance manifolds
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Video-based face recognition using adaptive hidden markov models
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Person recognition using human head motion information
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Face recognition with the multiple constrained mutual subspace method
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Video-Based face recognition using bayesian inference model
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Video-Based face recognition using earth mover's distance
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Video-Based face recognition using a metric of average euclidean distance
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
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Face recognition in videos is a hot topic in computer vision and biometrics over many years. Compared to traditional face analysis, video based face recognition has advantages of more abundant information to improve accuracy and robustness, but also suffers from large scale variations, low quality of facial images, illumination changes, pose variations and occlusions. Related to applications, we divide the existing video based face recognition approaches into two categories: videoimage based methods and video-video based methods, which are surveyed and analyzed in this paper.