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Proceedings Paper

Recognizing persons in images by learning from videos
Author(s): Eva Hörster; Jochen Lux; Rainer Lienhart
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Paper Abstract

In this paper, we propose an approach for automatically recognizing persons in images based on their general outer appearance. Therefore we build a statistical model for each person. Large amounts of training data are collected and labeled automatically by using a visual sensor array capturing image sequences containing the person to be learnt. Foreground-background segementation is performed to seperate the person from background, thus enabeling to learn the persons appearance independent of the background. Color and gradient features are extracted representing the segmented person. Person recognition of incoming photos is carried out using (k)- Nearest Neighbor(s) classification and the normalized histogram intersection match value is used as distance measure. Reported experimental results show that the presented approach performs well.

Paper Details

Date Published: 29 January 2007
PDF: 9 pages
Proc. SPIE 6506, Multimedia Content Access: Algorithms and Systems, 65060D (29 January 2007); doi: 10.1117/12.705200
Show Author Affiliations
Eva Hörster, Univ. of Augsburg (Germany)
Jochen Lux, Univ. of Augsburg (Germany)
Rainer Lienhart, Univ. of Augsburg (Germany)


Published in SPIE Proceedings Vol. 6506:
Multimedia Content Access: Algorithms and Systems
Alan Hanjalic; Raimondo Schettini; Nicu Sebe, Editor(s)

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