Quality based frame selection for face clustering in news video

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.

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Abstract

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.

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ID Code: 66205
Item Type: Conference Paper
Refereed: No
Keywords: Face Clustering, Face Recognition
DOI: 10.1109/DICTA.2013.6691517
ISBN: 9781479921263
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2013 IEEE
Deposited On: 15 Jan 2014 23:59
Last Modified: 24 Jun 2014 19:36

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