Video based face recognition using graph matching

Authors:
Gayathri Mahalingam;Chandra Kambhamettu
Affiliations:
Video/Image Modeling and Synthesis Laboratory, Department of Computer and Information Sciences, University of Delaware, Newark, DE;Video/Image Modeling and Synthesis Laboratory, Department of Computer and Information Sciences, University of Delaware, Newark, DE
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Year:
2010

Citing 13
Cited 1

Face Recognition by Elastic Bunch Graph Matching

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Generalized Local Binary Pattern Operator for Multiresolution Gray Scale and Rotation Invariant Texture Classification

ICAPR '01 Proceedings of the Second International Conference on Advances in Pattern Recognition
Bayesian face recognition using deformable intensity surfaces

CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Face Recognition from Video: A CONDENSATION Approach

FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Probabilistic recognition of human faces from video

Computer Vision and Image Understanding - Special issue on Face recognition
Face recognition: A literature survey

ACM Computing Surveys (CSUR)
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
A Video Database of Moving Faces and People

IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Feature Matching For Face Recognition

CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Eigenfaces for recognition

Journal of Cognitive Neuroscience
Visual tracking and recognition using probabilistic appearance manifolds

Computer Vision and Image Understanding
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
3D model-based face recognition in video

ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics

Face recognition in videos using adaptive graph appearance models

ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a novel graph based approach for still-to-video based face recognition, in which the temporal and spatial information of the face from each frame of the video is utilized. The spatial information is incorporated using a graph based face representation. The graphs contain information on the appearance and geometry of facial feature points and are labeled using the feature descriptors of the feature points. The temporal information is captured using an adaptive probabilistic appearance model. The recognition is performed in two stages where in the first stage a Maximum a Posteriori solution based on PCA is computed to prune the search space and select fewer candidates. A simple deterministic algorithm which exploits the topology of the graph is used for matching in the second stage. The experimental results on the UTD database and our dataset show that the adaptive matching and the graph based representation provides robust performance in recognition.