skip to main content
10.1145/2184512.2184570acmconferencesArticle/Chapter ViewAbstractPublication Pagesacm-seConference Proceedingsconference-collections
research-article

Dynamic subset selection for multi-camera tracking

Published: 29 March 2012 Publication History

Abstract

While multi-camera methods for object tracking tend to out-perform their single-camera counterparts, the data aggregation schemes can introduce new challenges, such as resource management and algorithm complexity. We present a framework for dynamically choosing the best subset of available cameras for tracking in real-time, which reduces aggregate tracking error and resource consumption and can be applied to a variety of existing base tracking models. We demonstrate on challenging video sequences of players in a basketball game. Our method is able to successfully track targets entering and exiting camera views and through occlusions, and overcome instances of single-view tracking drift.

References

[1]
N. G. Arnaud Doucet, Nando de Freitas. Sequential Monte Carlo Methods in Practice, chapter An introduction to Sequential Monte Carlo Methods, pages 3--14. Springer-Verlag, 2001.
[2]
Q. Cai and J. Aggarwal. Tracking human motion in structured environments using a distributed-camera system. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(11):1241--1247, Nov 1999.
[3]
D. Comaniciu, V. Ramesh, and P. Meer. Kernel-based object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 25:564--575, 2003.
[4]
A. Criminisi, I. Reid, and A. Zisserman. Single view metrology. Intl J. of Computer Vision, 40:123--148, 2000.
[5]
D. Delannay, N. Danhier, and C. De Vleeschouwer. Detection and recognition of sports(wo)men from multiple views. In International Conference on Distributed Smart Cameras, pages 1--7, Sept 2009.
[6]
W. Du and J. Piater. Multi-camera people tracking by collaborative particle filters and principal axis-based integration. In Asian Conference on Computer Vision, pages 365--374, 2007.
[7]
F. Fleuret, J. Berclaz, R. Lengagne, and P. Fua. Multicamera people tracking with a probabilistic occupancy map. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30:267--282, 2008.
[8]
B. Han, S.-W. Joo, and L. Davis. Multi-camera tracking with adaptive resource allocation. Intl J. of Computer Vision, 91:45--58, 2011.
[9]
T. Kailath. The divergence and Bhattacharyya distance measures in signal selection. IEEE Trans. on Comm. Tech., 15(1):52--60, 1967.
[10]
D. Karuppiah, R. Grupen, Z. Zhu, and A. Hanson. Automatic resource allocation in a distributed camera network. Machine Vision and Applications, 21:517--528, 2010.
[11]
S. Khan and M. Shah. A multiview approach to tracking people in crowded scenes using a planar homography constraint. In European Conference on Computer Vision, volume 3954 of Lecture Notes in Computer Science, pages 133--146. Springer Berlin/Heidelberg, 2006.
[12]
S. Khan and M. Shah. Tracking multiple occluding people by localizing on multiple scene planes. IEEE Trans. on Pattern Analysis and Machine Intelligence, pages 505--519, 2008.
[13]
A. Mittal and L. S. Davis. M2Tracker: a multi-view approach to segmenting and tracking people in a cluttered scene. Intl J. of Computer Vision, 51:189--203, 2003.
[14]
K. Nummiaro, E. Koller-Meier, T. Svoboda, D. Roth, and L. V. Gool. Color-based object tracking in multi-camera environments. Lecture Notes in Computer Science, 2781:591--599, 2003.
[15]
M. Taj and A. Cavallaro. Distributed and decentralized multi-camera tracking: a survey. IEEE Signal Processing Magazine, 28(3), 2011.
[16]
A. Yilmaz, O. Javed, and M. Shah. Object tracking: A survey. ACM Comput. Surv., 38, December 2006.
[17]
Q. Zhou and J. Aggarwal. Object tracking in an outdoor environment using fusion of features and cameras. Image and Vision Computing, 24(11):1244--1255, 2006.

Cited By

View all
  • (2015)Dynamic task decomposition for decentralized object tracking in complex scenesComputer Vision and Image Understanding10.1016/j.cviu.2015.02.007134:C(89-104)Online publication date: 1-May-2015
  • (2014)Wide-area Multi-camera Multi-object Tracking with Dynamic Task DecompositionProceedings of the International Conference on Distributed Smart Cameras10.1145/2659021.2659033(1-6)Online publication date: 4-Nov-2014

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
ACMSE '12: Proceedings of the 50th annual ACM Southeast Conference
March 2012
424 pages
ISBN:9781450312035
DOI:10.1145/2184512
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2012

Permissions

Request permissions for this article.

Check for updates

Qualifiers

  • Research-article

Conference

ACM SE '12
Sponsor:
ACM SE '12: ACM Southeast Regional Conference
March 29 - 31, 2012
Alabama, Tuscaloosa

Acceptance Rates

ACMSE '12 Paper Acceptance Rate 28 of 56 submissions, 50%;
Overall Acceptance Rate 502 of 1,023 submissions, 49%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 05 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2015)Dynamic task decomposition for decentralized object tracking in complex scenesComputer Vision and Image Understanding10.1016/j.cviu.2015.02.007134:C(89-104)Online publication date: 1-May-2015
  • (2014)Wide-area Multi-camera Multi-object Tracking with Dynamic Task DecompositionProceedings of the International Conference on Distributed Smart Cameras10.1145/2659021.2659033(1-6)Online publication date: 4-Nov-2014

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media