Person-based video summarization and retrieval by tracking and clustering temporal face sequences

Tong Zhang; Di Wen; Xiaoqing Ding

doi:10.1117/12.2009127

21 March 2013 Person-based video summarization and retrieval by tracking and clustering temporal face sequences

Tong Zhang, Di Wen, Xiaoqing Ding

Proceedings Volume 8664, Imaging and Printing in a Web 2.0 World IV; 86640O (2013) https://doi.org/10.1117/12.2009127
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

People are often the most important subjects in videos. It is highly desired to automatically summarize the occurrences of different people in a large collection of video and quickly find the video clips containing a particular person among them. In this paper, we present a person-based video summarization and retrieval system named VideoWho which extracts temporal face sequences in videos and groups them into clusters, with each cluster containing video clips of the same person. This is accomplished based on advanced face detection and tracking algorithms, together with a semisupervised face clustering approach. The system achieved good clustering accuracy when tested on a hybrid video set including home video, TV plays and movies. On top of this technology, a number of applications can be built, such as automatic summarization of major characters in videos, person-related video search on the Internet and personalized UI systems etc.

Citation Download Citation

Tong Zhang, Di Wen, and Xiaoqing Ding "Person-based video summarization and retrieval by tracking and clustering temporal face sequences", Proc. SPIE 8664, Imaging and Printing in a Web 2.0 World IV, 86640O (21 March 2013); https://doi.org/10.1117/12.2009127

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