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A Multi-configuration Part-based Person Detector
Citation key 1452García-Martín2014
Author Álvaro García-Martín and Rubén Heras Evangelio and Thomas Sikora
Title of Book International Conference on Signal Processing and Multimedia Applications, SIGMAP
Pages 321–328
Year 2014
DOI 10.5220/0005126703210328
Address Vienna, Austria
Month aug
Publisher SCITEPRESS Digital Library
Abstract People detection is a task that has generated a great interest in the computer vision and specially in the surveillance community. One of the main problems of this task in crowded scenarios is the high number of occlusions deriving from persons appearing in groups. In this paper, we address this problem by combining individual body part detectors in a statistical driven way in order to be able to detect persons even in case of failure of any detection of the body parts, i.e., we propose a generic scheme to deal with partial occlusions. We demonstrate the validity of our approach and compare it with other state of the art approaches on several public datasets. In our experiments we consider sequences with different complexities in terms of occupation and therefore with different number of people present in the scene, in order to highlight the benefits and difficulties of the approaches considered for evaluation. The results show that our approach improves the results provided by state of the art approaches specially in the case of crowded scenes.
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