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Sensors 2014, 14(2), 3130-3155; doi:10.3390/s140203130

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

1
Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2
Shanghai Key Laboratory of Digital Media Processing and Transmissions, Shanghai 200240, China
3
Department of Electronics Engineering, Dalian Maritime University, Dalian 116026, China
4
Bocom Smart Network Technologies Inc., Shanghai 200233, China
*
Author to whom correspondence should be addressed.
Received: 19 December 2013 / Revised: 9 January 2014 / Accepted: 12 February 2014 / Published: 17 February 2014
(This article belongs to the Section Physical Sensors)
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Abstract

To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks.
Keywords: appearance model; object tracking; sparse representation; structured dictionary learning; Bayesian inference; visual sensor networks appearance model; object tracking; sparse representation; structured dictionary learning; Bayesian inference; visual sensor networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Xue, M.; Yang, H.; Zheng, S.; Zhou, Y.; Yu, Z. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking. Sensors 2014, 14, 3130-3155.

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