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Cluster-Based Distributed Face Tracking in Camera Networks

Title: Cluster-Based Distributed Face Tracking in Camera Networks
Authors: Josiah Yoder; Henry Medeiros; Johnny Park; Avinash C. Kak
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://cobweb.ecn.purdue.edu/RVL/Publications/Yoder10ClusterBased.pdf.
Collection: CiteSeerX
Description: —In this paper, we present a distributed multicamera face tracking system suitable for large wired camera networks. Unlike previous multicamera face tracking systems, our system does not require a central server to coordinate the entire tracking effort. Instead, an efficient camera clustering protocol is used to dynamically form groups of cameras for in-network tracking of individual faces. The clustering protocol includes cluster propagation mechanisms that allow the computational load of face tracking to be transferred to different cameras as the target objects move. Furthermore, the dynamic election of cluster leaders provides robustness against system failures. Our experimental results show that our cluster-based distributed face tracker is capable of accurately tracking multiple faces in real-time. The overall performance of the distributed system is comparable to that of a centralized face tracker, while presenting the advantages of scalability and robustness. Index Terms—Camera networks, distributed tracking, face tracking, object detection. I.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.97; http://cobweb.ecn.purdue.edu/RVL/Publications/Yoder10ClusterBased.pdf
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.97; http://cobweb.ecn.purdue.edu/RVL/Publications/Yoder10ClusterBased.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.32B46EF
Database: BASE