Graduate School and Research Center in Digital Sciences

Crowd density map estimation based on feature tracks

Fradi, Hajer; Dugelay, Jean-Luc

MMSP 2013, 15th International Workshop on Multimedia Signal Processing, September 30-October 2, 2013, Pula, Italy

Crowd density analysis is a crucial component in visual surveillance mainly for security monitoring. This paper proposes a novel approach for crowd density measure, in which local information at pixel level substitutes a global crowd level or a number of people per-frame. The proposed approach consists of generating fully automatic and crowd density maps using local features as an observation of a probabilistic crowd function. It also involves a feature tracking step which allows excluding feature points belonging to the background. This process is favorable for the later density function estimation since the influence of features irrelevant to the underlying crowd density is removed. Our proposed approach is evaluated on videos from different datasets, and the results demonstrate the effectiveness of feature tracks for crowd estimation. Furthermore, we include a comparative study between different local features in order to investigate their discriminative power to the crowd.

Document Doi Bibtex

Title:Crowd density map estimation based on feature tracks
Type:Conference
Language:English
City:Pula
Country:ITALY
Date:
Department:Digital Security
Eurecom ref:4043
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Bibtex: @inproceedings{EURECOM+4043, doi = {http://dx.doi.org/10.1109/MMSP.2013.6659261}, year = {2013}, title = {{C}rowd density map estimation based on feature tracks}, author = {{F}radi, {H}ajer and {D}ugelay, {J}ean-{L}uc}, booktitle = {{MMSP} 2013, 15th {I}nternational {W}orkshop on {M}ultimedia {S}ignal {P}rocessing, {S}eptember 30-{O}ctober 2, 2013, {P}ula, {I}taly}, address = {{P}ula, {ITALY}}, month = {09}, url = {http://www.eurecom.fr/publication/4043} }
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