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Sensors 2014, 14(6), 9380-9407; doi:10.3390/s140609380

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

1
Institute Charles Delaunay, Université de Technologie de Troyes, 12 rue Marie Curie, CS 42060,10004 TROYES CEDEX, France
2
Laboratory Heudiasyc, Université de Technologie de Compiègne, Rue Roger Couttolenc, CS 60319,60203 COMPIEGNE CEDEX, France
*
Author to whom correspondence should be addressed.
Received: 2 December 2013 / Revised: 17 May 2014 / Accepted: 20 May 2014 / Published: 26 May 2014
(This article belongs to the Section Physical Sensors)
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Abstract

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. View Full-Text
Keywords: visual tracking; region descriptor; appearance model updating; clustering visual tracking; region descriptor; appearance model updating; clustering
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

Qin, L.; Snoussi, H.; Abdallah, F. Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance. Sensors 2014, 14, 9380-9407.

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