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Authors: Houda Maâmatou 1 ; Thierry Chateau 2 ; Sami Gazzah 3 ; Yann Goyat 4 and Najoua Essoukri Ben Amara 3

Affiliations: 1 Blaise Pascal University, University of Sousse and Logiroad, France ; 2 Blaise Pascal University, France ; 3 University of Sousse, Tunisia ; 4 Logiroad, France

Keyword(s): Transductive Transfer Learning, Specialization, Generic Classifier, Pedestrian Detection, Sequential Monte Carlo Filter (SMC).

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: In this paper, we tackle the problem of domain adaptation to perform object-classification and detection tasks in video surveillance starting by a generic trained detector. Precisely, we put forward a new transductive transfer learning framework based on a sequential Monte Carlo filter to specialize a generic classifier towards a specific scene. The proposed algorithm approximates iteratively the target distribution as a set of samples (selected from both source and target domains) which feed the learning step of a specialized classifier. The output classifier is applied to pedestrian detection into a traffic scene. We have demonstrated by many experiments, on the CUHK Square Dataset and the MIT Traffic Dataset, that the performance of the specialized classifier outperforms the generic classifier and that the suggested algorithm presents encouraging results.

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Paper citation in several formats:
Maâmatou, H. ; Chateau, T. ; Gazzah, S. ; Goyat, Y. and Essoukri Ben Amara, N. (2016). Transductive Transfer Learning to Specialize a Generic Classifier Towards a Specific Scene. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP; ISBN 978-989-758-175-5; ISSN 2184-4321, SciTePress, pages 411-422. DOI: 10.5220/0005725104110422

@conference{visapp16,
author={Houda Maâmatou and Thierry Chateau and Sami Gazzah and Yann Goyat and Najoua {Essoukri Ben Amara}},
title={Transductive Transfer Learning to Specialize a Generic Classifier Towards a Specific Scene},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP},
year={2016},
pages={411-422},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005725104110422},
isbn={978-989-758-175-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - Volume 4: VISAPP
TI - Transductive Transfer Learning to Specialize a Generic Classifier Towards a Specific Scene
SN - 978-989-758-175-5
IS - 2184-4321
AU - Maâmatou, H.
AU - Chateau, T.
AU - Gazzah, S.
AU - Goyat, Y.
AU - Essoukri Ben Amara, N.
PY - 2016
SP - 411
EP - 422
DO - 10.5220/0005725104110422
PB - SciTePress