Date of Award
Fall 2013
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Electrical and Computer Engineering
First Advisor
Johnny Park
Committee Chair
Johnny Park
Committee Co-Chair
Hong Z. Tan
Committee Member 1
Henry Medeiros
Committee Member 2
Mireille Boutin
Abstract
The proliferation of miniaturized low-power computing devices, advances in wireless communications, and the availability of inexpensive imaging sensors have enabled the development of wireless camera networks (WCN). In this dissertation, we consider the problem of real-time object tracking with a WCN. Existing object tracking methods designed for multi-camera systems do not take into account the unique constraints of WCNs. Specifically, an effective object tracking system for WCNs must anticipate unreliable network communication, limited memory, and limited computational power in each camera node. In particular, unreliable communication degrades the quality of the visual information shared by the cameras, which ultimately degrades the tracking performance in the network. We present a novel resource-aware framework for the implementation of distributed particle filters in resource-constrained WCNs. Our method focuses on the effects of communication failures on object tracking performance by adjusting the amount of data packets generated and transmitted by the cameras according to the network conditions. We demonstrate the performance of the proposed framework using three different mechanisms to share the particle information among nodes: synchronized particles, Gaussian mixture models, and Parzen windows. We show that all three approaches benefit from the proposed resource-aware mechanism in terms of tracking accuracy or energy efficiency.
Recommended Citation
Hong, Kihyun, "Resource-Aware Distributed Particle Filtering for Cluster-Based Object Tracking in Wireless Camera Networks" (2013). Open Access Dissertations. 142.
https://docs.lib.purdue.edu/open_access_dissertations/142