Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
The LIMSI Broadcast News transcription system
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Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Name-It: Association of Face and Name in Video
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Visual identification of people by computer
Visual identification of people by computer
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Face recognition: component-based versus global approaches
Computer Vision and Image Understanding - Special issue on Face recognition
Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
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Distinctive Image Features from Scale-Invariant Keypoints
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Recognizing Frontal Face Images Using Hidden Markov Models with One Training Image per Person
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
Acquiring Linear Subspaces for Face Recognition under Variable Lighting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
ImprovingWeb-based Image Search via Content Based Clustering
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
On the Use of SIFT Features for Face Authentication
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Face recognition from a single image per person: A survey
Pattern Recognition
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ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Selecting discriminant eigenfaces for face recognition
Pattern Recognition Letters
Automatic detection and recognition of players in soccer videos
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Person spotting: video shot retrieval for face sets
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Travelmedia: An intelligent management system for media captured in travel
Journal of Visual Communication and Image Representation
Automatic Face Annotation in News Images by Mining the Web
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Face Recognition from Caption-Based Supervision
International Journal of Computer Vision
Facing scalability: Naming faces in an online social network
Pattern Recognition
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In this study, we propose a method for finding people in large news photograph and video collections. Our method exploits the multi-modal nature of these data sets to recognize people and does not require any supervisory input. It first uses the name of the person to populate an initial set of candidate faces. From this set, which is likely to include the faces of other people, it selects the group of most similar faces corresponding to the queried person in a variety of conditions. Our main contribution is to transform the problem of recognizing the faces of the queried person in a set of candidate faces to the problem of finding the highly connected sub-graph (the densest component) in a graph representing the similarities of faces. We also propose a novel technique for finding the similarities of faces by matching interest points extracted from the faces. The proposed method further allows the classification of new faces without needing to re-build the graph. The experiments are performed on two data sets: thousands of news photographs from Yahoo! news and over 200 news videos from TRECVid2004. The results show that the proposed method provides significant improvements over text-based methods.