Quality based frame selection for face clustering in news video
Data(s) |
2013
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Resumo |
Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance. |
Formato |
application/pdf |
Identificador | |
Publicador |
IEEE |
Relação |
http://eprints.qut.edu.au/66205/1/DICTA13.pdf DOI:10.1109/DICTA.2013.6691517 Anantharajah, Kaneswaran, Denman, Simon, Tjondronegoro, Dian, Sridharan, Sridha, Fookes, Clinton, & Guo, Xufeng (2013) Quality based frame selection for face clustering in news video. In 2013 International Conference on Digital Image Computing : Techniques and Applications (DICTA), IEEE, Hobart, TAS. http://purl.org/au-research/grants/ARC/LP0991238 |
Direitos |
Copyright 2013 IEEE |
Fonte |
Science & Engineering Faculty |
Palavras-Chave | #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #080106 Image Processing #Face Clustering #Face Recognition |
Tipo |
Conference Paper |