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Communication Dans Un Congrès Année : 2013

Person Detection with a Computation Time Weighted AdaBoost

Résumé

In this paper, a boosted cascade person detection framework with heterogeneous pool of features is presented. The boosted cascade construction and feature selection is carried out using a modified AdaBoost that takes computation time of features into consideration. The final detector achieves a low Miss Rate of 0.06 at 10−3 False Positive Per Window on the INRIA public dataset while achieving an average speed up of 1.8x on the classical variant.
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Dates et versions

hal-00912829 , version 1 (02-12-2013)

Identifiants

Citer

Alhayat Ali Mekonnen, Frédéric Lerasle, Ariane Herbulot. Person Detection with a Computation Time Weighted AdaBoost. Advanced Concepts for Intelligent Vision Systems (ACIVS), Oct 2013, Poznan, Poland. pp.632-644, ⟨10.1007/978-3-319-02895-8_57⟩. ⟨hal-00912829⟩
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