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Video Indexing Using Face Detection and Face Recognition Methods (2008)

Abstract
This paper presents a video indexing approach, that combines face detection and face recognition. The frames of the video sequences are scanned for faces by a Neural Network based face detector and the faces are extracted from the sequence. The faces are then grouped into clusters by a combination of a face recognition method using pseudo two-dimensional Hidden Markov Models and the k-means clustering algorithm. Each resulting cluster consists of the face images of the one person. In the next step the detected faces are labeled as one of the different people in the video sequence and the occurrence of the people can be evaluated. The results of the proposed approach on a TV broadcast news sequence are presented. The system was able to distinguish between three different newscasters and an interviewed person. 1

Publication details
Download http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.9335
Source http://www.mmk.e-technik.tu-muenchen.de/~waf/publ/99/wiamis99.pdf
Contributors CiteSeerX
Repository CiteSeerX - Scientific Literature Digital Library and Search Engine (United States)
Type text
Language English
Relation 10.1.1.110.5546, 10.1.1.120.610, 10.1.1.41.5727, 10.1.1.31.3497