Soccer players identification based on visual local features
Proceedings of the 6th ACM international conference on Image and video retrieval
Naming faces in broadcast news video by image google
MM '08 Proceedings of the 16th ACM international conference on Multimedia
A Graph Based Approach to Speaker Retrieval in Talk Show Videos with Transcript-Based Supervision
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
An experimental study on content-based face annotation of photos
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Automatic detection and recognition of players in soccer videos
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Face recognition with DAISY descriptors
Proceedings of the 12th ACM workshop on Multimedia and security
Identifying persons in news article images based on textual analysis
ICADL'10 Proceedings of the role of digital libraries in a time of global change, and 12th international conference on Asia-Pacific digital libraries
Multiple instance metric learning from automatically labeled bags of faces
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Retrieval-based face annotation by weak label regularized local coordinate coding
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Face Recognition from Caption-Based Supervision
International Journal of Computer Vision
Lightweight automatic face annotation in media pages
Proceedings of the 21st international conference on World Wide Web
A unified learning framework for auto face annotation by mining web facial images
Proceedings of the 21st ACM international conference on Information and knowledge management
Learning to name faces: a multimodal learning scheme for search-based face annotation
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Annotation propagation in image databases using similarity graphs
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Naming persons in video: Using the weak supervision of textual stories
Journal of Visual Communication and Image Representation
Automatic name-face alignment to enable cross-media news retrieval
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We propose a method to associate names and faces for querying people in large news photo collections. On the assumption that a person's face is likely to appear when his/her name is mentioned in the caption, first all the faces associated with the query name are selected. Among these faces, there could be many faces corresponding to the queried person in different conditions, poses and times, but there could also be other faces corresponding to other people in the caption or some non-face images due to the errors in the face detection method used. However, in most cases, the number of corresponding faces of the queried person will be large, and these faces will be more similar to each other than to others. In this study, we propose a graph based method to find the most similar subset among the set of possible faces associated with the query name, where the most similar subset is likely to correspond to the faces of the queried person. When the similarity of faces are represented in a graph structure, the set of most similar faces will be the densest component in the graph. We represent the similarity of faces using SIFT descriptors. The matching interest points on two faces are decided after the application of two constraints, namely the geometrical constraint and the unique match constraint. The average distance of the matching points are used to construct the similarity graph. The most similar set of faces is then found based on a greedy densest component algorithm. The experiments are performed on thousands of news photographs taken in real life conditions and, therefore, having a large variety of poses, illuminations and expressions.