Video shot classification using human faces

Yin Chan, Shang Hung Lin, Yap Peng Tan, Sun-Yuan Kung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

People usually make up a lot of information contents in videos. The abilities to answer queries and facilitate browsing related to people in videos are crucial. In a single video sequence, a particular person may appear multiple number of times. In this paper, we propose a scheme to automatically detect the repeated occurrences of the same people to enable fast people related searching. In particular, we propose a video shot classification scheme using human faces, regardless of scale and background. Video shots are classified by clustering facial features extracted from these shots. Potential applications include video indexing and browsing. Employing unsupervised clustering algorithms, this scheme requires no human intervention. Experimental results on a 4-minute news sequence show that it achieves encouraging results (cf. figures 4 & 5).

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Editors Anon
PublisherIEEE
Pages843-846
Number of pages4
Volume3
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: Sep 16 1996Sep 19 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz
Period9/16/969/19/96

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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