Graduate School and Research Center in Digital Sciences

Enhancing human detection using crowd density measures and an adaptive correction filter

Eiselein, Volker; Fradi, Hajer; Keller, Ivo; Sikora, Thomas; Dugelay, Jean-Luc

AVSS 2013, 10th IEEE International Conference on Advanced Video and Signal-Based Surveillance, August 27-30, 2013, Krakow, Poland

In this paper we improve a human detector by means of crowd density information. Human detection is especially challenging in crowded scenes which makes it important to introduce additional knowledge into the detection process. We compute crowd density maps in order to estimate the spatial distribution of people in the scene and show how it is possible to enhance the detection results of a state-of-the-art human detector using this information. The proposed method applies a self-adaptive, dynamic parametrization and as an additional contribution uses scene-adaptive learning of the human aspect ratio in order to reduce false positive detections in crowded areas. We evaluate our method on videos from different datasets and demonstrate how our system achieves better results than the baseline algorithm.

Document Doi Bibtex

Title:Enhancing human detection using crowd density measures and an adaptive correction filter
Type:Conference
Language:English
City:Krakow
Country:POLAND
Date:
Department:Digital Security
Eurecom ref:4046
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Bibtex: @inproceedings{EURECOM+4046, doi = {http://dx.doi.org/10.1109/AVSS.2013.6636610}, year = {2013}, title = {{E}nhancing human detection using crowd density measures and an adaptive correction filter}, author = {{E}iselein, {V}olker and {F}radi, {H}ajer and {K}eller, {I}vo and {S}ikora, {T}homas and {D}ugelay, {J}ean-{L}uc}, booktitle = {{AVSS} 2013, 10th {IEEE} {I}nternational {C}onference on {A}dvanced {V}ideo and {S}ignal-{B}ased {S}urveillance, {A}ugust 27-30, 2013, {K}rakow, {P}oland}, address = {{K}rakow, {POLAND}}, month = {08}, url = {http://www.eurecom.fr/publication/4046} }
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