Papers by Dinesh Elayaperumal
Journal of Visual Communication and Image Representation, Jul 1, 2020
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Information Sciences
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Journal of Electrical Engineering & Technology
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Journal of Visual Communication and Image Representation, 2020
Abstract This paper presents a novel sparse context-aware spatio-temporal correlation filter trac... more Abstract This paper presents a novel sparse context-aware spatio-temporal correlation filter tracker (SCAST) method for robust visual object tracking. Different from the existing trackers, this paper introduce an l 1 multi-scale regularization parameter-based correlation filter that reduces the boundary effect due to partial occlusions, illumination and scale variations. At each iteration, the l 1 regularization parameter is updated through spatial knowledge of each correlation filter coefficient. Besides, the contextual information acquired from the target region can lead to determining the accurate localization of the target. Moreover, contextual information has combined with spatio-temporal factor to achieve the better performance. Further, an objective function is designed with system constraints to ensure the applicability of the model and the optimal solution is derived by utilizing the alternating direction method of multiplier, which leads to low computational cost. Finally, the feasibility and superiority of proposed tracker algorithm is evaluated through three benchmark dataset: OTB-2013, OTB-2015, and TempleColor-128.
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With the emergence of camera technology, visual tracking has witnessed great attention in the fie... more With the emergence of camera technology, visual tracking has witnessed great attention in the field of computer vision . For instance, numerous discriminative correlation filter (DCF) methods are broadly used in tracking, nevertheless, most of them fail to efficiently find the target in challenging situations which leads to tracking failure throughout the sequences. In order to handle these issues, we propose contextual information based spatial variation with a multi-feature fusion method (CSVMF) for robust object tracking. This work incorporates the contextual information of the target to determine the location of the target accurately, which utilizes the relationship between the target and its surroundings to increase the efficiency of the tracker. In addition, we integrate the spatial variation information which measures the second-order difference of the filter to avoid the over-fitting problem caused by the changes in filter coefficient . Furthermore, we adopt multi-feature fu...
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Pattern Recognition
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Papers by Dinesh Elayaperumal