Model-based validation approaches and matching techniques for automotive vision based pedestrian detection

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Model-based validation approaches and matching techniques for automotive vision based pedestrian detection

Model-based validation approaches and matching techniques for automotive vision based pedestrian detection

Broggi, A. / Fascioli, A. / Grisleri, P. / Graf, T. / Meinecke, M.

Pedestrian detection is a challenging vision task, especially applied to the automotive field where the background changes as the vehicle moves. This paper presents an extensive study upon human body models and the techniques suitable for being used in a pedestrian detection system. Several different approaches for building model sets, such as synthetic, real, and dynamic sets are presented and discussed. Comparative results are reported with reference to a case study of a real system. Preliminary results of current research status are shown together with further developments.

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Title :

Model-based validation approaches and matching techniques for automotive vision based pedestrian detection

Contributors:

Broggi, A. (author) / Fascioli, A. (author) / Grisleri, P. (author) / Graf, T. (author) / Meinecke, M. (author)

Published in:

2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops ; 1

Publication date :

2005-01-01

Size :

441017 byte

ISBN :

ISSN :

DOI :

https://doi.org/10.1109/CVPR.2005.495

Type of media :

Conference paper

Type of material :

Electronic Resource

Language :

English

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