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Efficient people re-identication based on models of human clothes

  • In this paper, we describe an efficient method for a fast people re-identification based on models of human clothes. An initial model is estimated during people detection and tracking, which will be refined during the re-identification. This stepwise extraction, combination and comparing of features speeds up the whole re-identification. For the refining, several saliency maps are used to extract individual features. These individual features are located separately for any human body part. The body parts are located with an optimized GPU-based HOG detector. Furthermore, we introduce a meanshift-based fusion concept which utilizes multiple detectors in order to increase the detection reliability.

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Author:Uwe Handmann, Sebastian Hommel, Darius Malysiak
Parent Title (English):15th IEEE International Symposium on Computational Intelligence and Informatics
Document Type:Conference Proceeding
Year of Completion:2014
Contributing Corporation:IEEE
Release Date:2019/06/25
Page Number:6
First Page:137
Last Page:142
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft
Licence (German):License LogoNo Creative Commons