Article

A Sampling Algorithm for Tracking Multiple Objects

Authors:

Hai Tao,

Harpreet S. Sawhney,

Rakesh KumarAuthors Info & Claims

ICCV '99: Proceedings of the International Workshop on Vision Algorithms: Theory and Practice

Pages 53 - 68

Published: 21 September 1999 Publication History

Abstract

The recently proposed CONDENSATION algorithm and its variants enable the estimation of arbitrary multi-modal posterior distributions that potentially represent multiple tracked objects. However, the specific state representation adopted in the earlier work does not explicitly supports counting, addition, deletion and occlusion of objects. Furthermore, the representation may increasingly bias the posterior density estimates towards objects with dominant likelihood as the estimation progresses over many frames. In this paper, a novel formulation and an associated CONDENSATION-like sampling algorithm that explicitly support counting, addition and deletion of objects are proposed. We represent all objects in an image as an object configuration. The a posteriori distribution of all possible configurations are explored and maintained using sampling techniques. The dynamics of configurations allow addition and deletion of objects and handle occlusion. An efficient hierarchical algorithm is also proposed to approximate the sampling process in high dimensional space. Promising comparative results on both synthetic and real data are demonstrated.

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Cited By

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Saravanakumar SVadivel AAhmed CJena SKumar RTuruk ADash M(2011)Multiple object tracking using HSV color spaceProceedings of the 2011 International Conference on Communication, Computing & Security10.1145/1947940.1947993(247-252)Online publication date: 12-Feb-2011
https://dl.acm.org/doi/10.1145/1947940.1947993
Palaio HBatista J(2009)A kernel particle filter multi-object tracking using Gabor-based region covariance matricesProceedings of the 16th IEEE international conference on Image processing10.5555/1819298.1819851(4033-4036)Online publication date: 7-Nov-2009
https://dl.acm.org/doi/10.5555/1819298.1819851
Xue JMa ZZheng N(2009)Hierarchical model for joint detection and tracking of multi-targetProceedings of the 9th Asian conference on Computer Vision - Volume Part II10.1007/978-3-642-12304-7_16(160-171)Online publication date: 23-Sep-2009
https://dl.acm.org/doi/10.1007/978-3-642-12304-7_16
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A Sampling Algorithm for Tracking Multiple Objects
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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ICCV '99: Proceedings of the International Workshop on Vision Algorithms: Theory and Practice

September 1999

376 pages

ISBN:3540679731

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Springer-Verlag

Berlin, Heidelberg

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Published: 21 September 1999

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Saravanakumar SVadivel AAhmed CJena SKumar RTuruk ADash M(2011)Multiple object tracking using HSV color spaceProceedings of the 2011 International Conference on Communication, Computing & Security10.1145/1947940.1947993(247-252)Online publication date: 12-Feb-2011
https://dl.acm.org/doi/10.1145/1947940.1947993
Palaio HBatista J(2009)A kernel particle filter multi-object tracking using Gabor-based region covariance matricesProceedings of the 16th IEEE international conference on Image processing10.5555/1819298.1819851(4033-4036)Online publication date: 7-Nov-2009
https://dl.acm.org/doi/10.5555/1819298.1819851
Xue JMa ZZheng N(2009)Hierarchical model for joint detection and tracking of multi-targetProceedings of the 9th Asian conference on Computer Vision - Volume Part II10.1007/978-3-642-12304-7_16(160-171)Online publication date: 23-Sep-2009
https://dl.acm.org/doi/10.1007/978-3-642-12304-7_16
Bernardin KStiefelhagen R(2008)Evaluating multiple object tracking performanceJournal on Image and Video Processing10.1155/2008/2463092008(1-10)Online publication date: 1-Jan-2008
https://dl.acm.org/doi/10.1155/2008/246309
Lin ZDavis LDoermann DDeMenthon D(2007)Simultaneous appearance modeling and segmentation for matching people under occlusionProceedings of the 8th Asian conference on Computer vision - Volume Part II10.5555/1775728.1775777(404-413)Online publication date: 18-Nov-2007
https://dl.acm.org/doi/10.5555/1775728.1775777
Qu WSchonfeld DMohamed M(2007)Distributed Bayesian multiple-target tracking in crowded environments using multiple collaborative camerasEURASIP Journal on Advances in Signal Processing10.1155/2007/383732007:1(21-21)Online publication date: 1-Jan-2007
https://dl.acm.org/doi/10.1155/2007/38373
Rathi YVaswani NTannenbaum AYezzi A(2007)Tracking Deforming Objects Using Particle Filtering for Geometric Active ContoursIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2007.108129:8(1470-1475)Online publication date: 1-Aug-2007
https://dl.acm.org/doi/10.1109/TPAMI.2007.1081
Bernardin KGehrig TStiefelhagen R(2006)Multi- and single view multiperson tracking for smart room environmentsProceedings of the 1st international evaluation conference on Classification of events, activities and relationships10.5555/1759639.1759646(81-92)Online publication date: 6-Apr-2006
https://dl.acm.org/doi/10.5555/1759639.1759646
Lanz O(2006)Approximate Bayesian Multibody TrackingIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2006.17728:9(1436-1449)Online publication date: 1-Sep-2006
https://dl.acm.org/doi/10.1109/TPAMI.2006.177
Xue JZheng NZhong X(2005)Sequential stratified sampling belief propagation for multiple targets trackingProceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I10.1007/11538059_35(330-339)Online publication date: 23-Aug-2005
https://dl.acm.org/doi/10.1007/11538059_35
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Multiple Human Objects Tracking in Crowded Scenes

Tracking Multiple Objects through Occlusions

Tracking multiple objects using multiple hypothesis tracking framework

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