Visual tracking via decision-based particle filtering based on sparse representation

Mohamad Hosein Davoodabadi Farahani; Mojtaba Lotfizad

doi:10.1117/1.JEI.27.4.043027

27 July 2018 Visual tracking via decision-based particle filtering based on sparse representation

Mohamad Hosein Davoodabadi Farahani, Mojtaba Lotfizad

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 4, 043027 (July 2018). https://doi.org/10.1117/1.JEI.27.4.043027

Abstract

Many approaches for effective object tracking have been proposed in the literature, among which the sparse representation has been a successful method for finding the best candidate with the minimal reconstruction error. We propose a generic object tracking algorithm using the sparse representation of the target’s local patches. Sparse codes are adopted as a confidence measure to avoid drifting from the target during tracking. Experiments demonstrate that mentioned confidence measure can specify appearance change of the target accurately. Furthermore, given this measure, we propose a double search scheme for tracking targets. By using this approach, the proposed tracker can work with fewer particles than its rivals and as a result does not suffer from the extracomputation of redundant particles in a scene with no particular challenge. Moreover, a simple yet effective online template update approach is adopted in order to overcome the challenges such as abrupt illumination variation, the manifestation of occlusion, blurriness, or sudden movements of the target. Both quantitative and qualitative evaluations on a challenging dataset demonstrate a favorable performance compared to several state-of-the-art algorithms in terms of accuracy and robustness.

Citation Download Citation

Mohamad Hosein Davoodabadi Farahani and Mojtaba Lotfizad "Visual tracking via decision-based particle filtering based on sparse representation," Journal of Electronic Imaging 27(4), 043027 (27 July 2018). https://doi.org/10.1117/1.JEI.27.4.043027

Received: 2 October 2017; Accepted: 10 July 2018; Published: 27 July 2018

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KEYWORDS

Optical tracking

Detection and tracking algorithms

Particles

Associative arrays

Particle filters

Electronic filtering

Motion models

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