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Video object tracking with differential structural similarity index.

Loza, Artur and Wang, Fanglin and Yang, Jie and Mihaylova, Lyudmila (2011) Video object tracking with differential structural similarity index. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Prague, pp. 1405-1408. ISBN 978-1-4577-0537-3

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Abstract

The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared with similar methods based on colour and edge histograms and Bhattacharyya distance. However, the combined use of the structural similarity and a particle filter results in increased computational complexity of the algorithm. In this paper, a novel fast approach for video tracking based on the structural similarity measure is presented. The tracking algorithm proposed determines the state of the target (location, size) based on the gradient ascent procedure applied to the structural similarity surface of the video frame, thus avoiding computationally expensive sampling of the state space. The new method, while being computationally less expensive, has shown higher accuracy compared with the standard mean shift algorithm and the SSIM Particle Filter (SSIM-PF) [1] and its performance is illustrated over real video sequences.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: Tracking ; structural similarity ; gradient ascent
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 40838
Deposited By: Dr L Mihaylov
Deposited On: 31 May 2011 09:16
Refereed?: No
Published?: Published
Last Modified: 23 Sep 2013 15:50
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/40838

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