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IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2
Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences
Breckenridge, Colorado
January 05-January 07
ISBN: 0-7695-2271-8
ASCII Text
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David Biliotti, Gianluca Antonini, Jean Philippe Thiran, "Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences," Applications of Computer Vision and the IEEE Workshop on Motion and Video Computing, IEEE Workshop on, vol. 2, pp. 50-57, IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2, 2005.
 
 
BibTex
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@article{ 10.1109/ACVMOT.2005.77,
author = {David Biliotti and Gianluca Antonini and Jean Philippe Thiran},
title = {Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences},
journal ={Applications of Computer Vision and the IEEE Workshop on Motion and Video Computing, IEEE Workshop on},
volume = {2},
year = {2005},
isbn = {0-7695-2271-8},
pages = {50-57},
doi = {http://doi.ieeecomputersociety.org/10.1109/ACVMOT.2005.77},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Applications of Computer Vision and the IEEE Workshop on Motion and Video Computing, IEEE Workshop on
TI - Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences
SN - 0-7695-2271-8
SP50
EP57
A1 - David Biliotti,
A1 - Gianluca Antonini,
A1 - Jean Philippe Thiran,
PY - 2005
KW - null
VL - 2
JA - Applications of Computer Vision and the IEEE Workshop on Motion and Video Computing, IEEE Workshop on
ER -
 
David Biliotti, University of Siena, Italy
Gianluca Antonini, Swiss Federal Institute of Technology, Lausanne, CH
Jean Philippe Thiran, Swiss Federal Institute of Technology, Lausanne, CH
In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a black box providing us the input data. The idea is to apply a hierarchical clustering algorithm, using different data representations and distance measures, as a post-processing step. The final goal is to reduce the difference between the number of tracked pedestrians and the real number of individuals present in the scene.
Citation:
David Biliotti, Gianluca Antonini, Jean Philippe Thiran, "Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences," wacv-motion, vol. 2, pp.50-57, IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2, 2005
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