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Authors: Isaac Martín De Diego ; Ignacio San Román ; Cristina Conde and Enrique Cabello

Affiliation: Rey Juan Carlos University, Spain

Keyword(s): VideoSurveillance, Re-identification, Kernels Combination, Bag of Features.

Related Ontology Subjects/Areas/Topics: Biometrics and Pattern Recognition ; Image and Video Processing, Compression and Segmentation ; Multimedia ; Multimedia Signal Processing ; Telecommunications

Abstract: A novel method for re-identification based on optimal features extraction in VideoSurveillance environments is presented in this paper. A high number of features are extracted for each detected person in a dataset obtained from a camera in a scenario. An evaluation of the relative discriminate power of each bag of features for each person is performed. We propose a forward method in a Support Vector framework to obtained the optimal individual bags of features. These bags of features are used in a new scenario in order to detect suspicious persons using the images from a non-overlapping camera. The results obtained demonstrate the promising potential of the presented approach.

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Paper citation in several formats:
Martín De Diego, I.; San Román, I.; Conde, C. and Cabello, E. (2017). WYA2: Optimal Individual Features Extraction for VideoSurveillance Re-identification. In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SIGMAP; ISBN 978-989-758-260-8; ISSN 2184-3236, SciTePress, pages 35-41. DOI: 10.5220/0006435400350041

@conference{sigmap17,
author={Isaac {Martín De Diego}. and Ignacio {San Román}. and Cristina Conde. and Enrique Cabello.},
title={WYA2: Optimal Individual Features Extraction for VideoSurveillance Re-identification},
booktitle={Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SIGMAP},
year={2017},
pages={35-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006435400350041},
isbn={978-989-758-260-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - SIGMAP
TI - WYA2: Optimal Individual Features Extraction for VideoSurveillance Re-identification
SN - 978-989-758-260-8
IS - 2184-3236
AU - Martín De Diego, I.
AU - San Román, I.
AU - Conde, C.
AU - Cabello, E.
PY - 2017
SP - 35
EP - 41
DO - 10.5220/0006435400350041
PB - SciTePress

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