Ecole d'ingénieur et centre de recherche en Sciences du numérique

A new multiclass SVM algorithm and its application to crowd density analysis using LBP features

Fradi, Hajer; Dugelay, Jean-Luc

ICIP 2013, IEEE International Conference on Image Processing, 15-18 September 2013, Melbourne, Australia

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Crowd density analysis is a crucial component in visual surveillance for security monitoring. In this paper, we propose to estimate crowd density at patch level, where the size of each patch varies in such way to compensate the effects of perspective distortions. The main contribution of this paper is two-fold: First, we propose to learn a discriminant subspace of the high-dimensional Local Binary Pattern (LBP) instead of using raw LBP feature vector. Second, an alternative algorithm for multiclass SVM based on relevance scores is proposed. The effectiveness of the proposed approach is evaluated on PETS dataset, and the results demonstrate the effect of low-dimensional compact representation of LBP on the classification accuracy. Also, the performance of the proposed multiclass SVM algorithm is compared to other frequently used algorithms for multi-classification problem and the proposed algorithm gives good results while reducing the complexity of the classification.

Document Doi Bibtex

Titre:A new multiclass SVM algorithm and its application to crowd density analysis using LBP features
Mots Clés:Crowd density, multiclass SVM, local binary pattern, dimensionality reduction
Type:Conférence
Langue:English
Ville:Melbourne
Pays:AUSTRALIE
Date:
Département:Sécurité numérique
Eurecom ref:4028
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Bibtex: @inproceedings{EURECOM+4028, doi = {http://dx.doi.org/10.1109/ICIP.2013.6738938}, year = {2013}, title = {{A} new multiclass {SVM} algorithm and its application to crowd density analysis using {LBP} features}, author = {{F}radi, {H}ajer and {D}ugelay, {J}ean-{L}uc}, booktitle = {{ICIP} 2013, {IEEE} {I}nternational {C}onference on {I}mage {P}rocessing, 15-18 {S}eptember 2013, {M}elbourne, {A}ustralia}, address = {{M}elbourne, {AUSTRALIE}}, month = {09}, url = {http://www.eurecom.fr/publication/4028} }
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