A sparsity-driven approach to multi-camera tracking in visual sensor networks

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Coşar, Serhan and Çetin, Müjdat (2013) A sparsity-driven approach to multi-camera tracking in visual sensor networks. In: 10th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS 2013), Krakow, Poland

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Official URL: http://dx.doi.org/10.1109/AVSS.2013.6636674


In this paper, a sparsity-driven approach is presented for multi-camera tracking in visual sensor networks (VSNs). VSNs consist of image sensors, embedded processors and wireless transceivers which are powered by batteries. Since the energy and bandwidth resources are limited, setting up a tracking system in VSNs is a challenging problem. Motivated by the goal of tracking in a bandwidth-constrained environment, we present a sparsity-driven method to compress the features extracted by the camera nodes, which are then transmitted across the network for distributed inference. We have designed special overcomplete dictionaries that match the structure of the features, leading to very parsimonious yet accurate representations. We have tested our method in indoor and outdoor people tracking scenarios. Our experimental results demonstrate how our approach leads to communication savings without significant loss in tracking performance.

Item Type:Papers in Conference Proceedings
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:23479
Deposited By:Müjdat Çetin
Deposited On:13 Jan 2014 15:08
Last Modified:01 Aug 2019 15:51

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