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Bayesian modeling of facial similarity
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Learning and Classification of Complex Dynamics
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The FERET Evaluation Methodology for Face-Recognition Algorithms
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On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Distortion Invariant Object Recognition in the Dynamic Link Architecture
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Principal Manifolds and Probabilistic Subspaces for Visual Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Automatic Video-based Person Authentication Using the RBF Network
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Non-intrusive Person Authentication for Access Control by Visual Tracking and Face Recognition
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Learning Graphical Models of Images, Videos and Their Spatial Transformations
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Parametrized structure from motion for 3D adaptive feedback tracking of faces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
PersonSpotter - Fast and Robust System for Human Detection, Tracking and Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Pattern Classification (2nd Edition)
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UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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IEEE Transactions on Image Processing
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MMUI '05 Proceedings of the 2005 NICTA-HCSNet Multimodal User Interaction Workshop - Volume 57
Top-down, bottom-up multivalued default reasoning for identity maintenance
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Multimodal person authentication using speech, face and visual speech
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Simultaneous Facial Action Tracking and Expression Recognition in the Presence of Head Motion
International Journal of Computer Vision
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Dynamic face recognition: From human to machine vision
Image and Vision Computing
A pose-wise linear illumination manifold model for face recognition using video
Computer Vision and Image Understanding
Real time face and mouth recognition using radial basis function neural networks
Expert Systems with Applications: An International Journal
Identity Management in Face Recognition Systems
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Person recognition using facial video information: A state of the art
Journal of Visual Languages and Computing
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Audio-video biometric recognition for non-collaborative access granting
Journal of Visual Languages and Computing
Three-dimensional face pose detection and tracking using monocular videos: tool and application
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
A vision-based system for display interaction
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Image and Vision Computing
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Computer Vision and Image Understanding
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Recognition of human faces: from biological to artificial vision
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Patch-based face recognition from video
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
On-line learning of mutually orthogonal subspaces for face recognition by image sets
IEEE Transactions on Image Processing
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Probabilistic identity characterization for face recognition
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Recognition of human faces using a gallery of still or video images and a probe set of videos is systematically investigated using a probabilistic framework. In still-to-video recognition, where the gallery consists of still images, a time series state space model is proposed to fuse temporal information in a probe video, which simultaneously characterizes the kinematics and identity using a motion vector and an identity variable, respectively. The joint posterior distribution of the motion vector and the identity variable is estimated at each time instant and then propagated to the next time instant, Marginalization over the motion vector yields a robust estimate of the posterior distribution of the identity variable. A computationally efficient sequential importance sampling (SIS) algorithm is developed to estimate the posterior distribution. Empirical results demonstrate that, due to the propagation of the identity variable over time, a degeneracy in posterior probability of the identity variable is achieved to give improved recognition. The gallery is generalized to videos in order to realize video-to-video recognition. An exemplar-based learning strategy is adopted to automatically select video representatives from the gallery, serving as mixture centers in an updated likelihood measure. The SIS algorithm is applied to approximate the posterior distribution of the motion vector, the identity variable, and the exemplar index, whose marginal distribution of the identity variable produces the recognition result. The model formulation is very general and it allows a variety of image representations and transformations. Experimental results using images/videos collected at UMD, NIST/USF, and CMU with pose/illumination variations illustrate the effectiveness of this approach for both still-to-video and video-to-video scenarios with appropriate model choices.