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Visual tracking using structural local DCT sparse appearance model with occlusion detection

Title:

Visual tracking using structural local DCT sparse appearance model with occlusion detection

Shreyamsha Kumar, B. K. ORCID: https://orcid.org/0000-0002-3781-0635, Swamy, M.N.S. ORCID: https://orcid.org/0000-0002-3989-5476 and Ahmad, M. Omair ORCID: https://orcid.org/0000-0002-2924-6659 (2018) Visual tracking using structural local DCT sparse appearance model with occlusion detection. Multimedia Tools and Applications, 78 (6). pp. 7243-7266. ISSN 1380-7501

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Official URL: https://doi.org/10.1007/s11042-018-6453-z

Abstract

In this paper, a structural local DCT sparse appearance model with occlusion detection is proposed for visual tracking in a particle filter framework. The energy compaction property of the 2D-DCT is exploited to reduce the size of the dictionary as well as that of the candidate samples so that the computational cost of l1-minimization can be lowered. Further, a holistic image reconstruction procedure is proposed for robust occlusion detection and used for appearance model update, thus avoiding the degradation of the appearance model in the presence of occlusion/outliers. Also, a patch occlusion ratio is introduced in the confidence score computation to enhance the tracking performance. Quantitative and qualitative performance evaluations on two popular benchmark datasets demonstrate that the proposed tracking algorithm generally outperforms several state-of-the-art methods.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Refereed:Yes
Authors:Shreyamsha Kumar, B. K. and Swamy, M.N.S. and Ahmad, M. Omair
Journal or Publication:Multimedia Tools and Applications
Date:8 August 2018
Funders:
  • Natural Sciences and Engineering Research Council of Canada (NSERC)
  • Regroupement Stratégique en Microsystèmes du Québec (ReSMiQ)
  • Ministère de l’Éducation, de l’Enseignement Supérieur et de la Recherche (MEESR) du Québec
Digital Object Identifier (DOI):10.1007/s11042-018-6453-z
Keywords:Visual tracking, Local DCT sparse appearance model, Holistic image reconstruction, Reconstruction error, Occlusion map, Observation model update
ID Code:985427
Deposited By: M. OMAIR AHMAD
Deposited On:22 May 2019 18:06
Last Modified:22 May 2019 18:06
Related URLs:

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