A framework for multi-object tracking over distributed wireless camera networks

Victor Gau; Jenq-Neng Hwang

doi:10.1117/12.863284

4 August 2010 A framework for multi-object tracking over distributed wireless camera networks

Victor Gau, Jenq-Neng Hwang

Proceedings Volume 7744, Visual Communications and Image Processing 2010; 77441L (2010) https://doi.org/10.1117/12.863284
Event: Visual Communications and Image Processing 2010, 2010, Huangshan, China

Abstract

In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

Citation Download Citation

Victor Gau and Jenq-Neng Hwang "A framework for multi-object tracking over distributed wireless camera networks", Proc. SPIE 7744, Visual Communications and Image Processing 2010, 77441L (4 August 2010); https://doi.org/10.1117/12.863284

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available