2018
DOI: 10.3390/app8112233
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Minimum Barrier Distance-Based Object Descriptor for Visual Tracking

Abstract: In most visual tracking tasks, the target is tracked by a bounding box given in the first frame. The complexity and redundancy of background information in the bounding box inevitably exist and affect tracking performance. To alleviate the influence of background, we propose a robust object descriptor for visual tracking in this paper. First, we decompose the bounding box into non-overlapping patches and extract the color and gradient histograms features for each patch. Second, we adopt the minimum barrier dis… Show more

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Cited by 1 publication
(1 citation statement)
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“…In SRDCFdecon [40] adaptive decontamination is used which adaptively learns the reliability of each training sample and eliminates the influence of contaminated ones. The minimum barrier distance (MBD) [41] is developed to mitigate the impact of background on the tracker accuracy. The MBD consider the dissimilarity value to weight the extracted feature at each target position.…”
Section: Related Workmentioning
confidence: 99%
“…In SRDCFdecon [40] adaptive decontamination is used which adaptively learns the reliability of each training sample and eliminates the influence of contaminated ones. The minimum barrier distance (MBD) [41] is developed to mitigate the impact of background on the tracker accuracy. The MBD consider the dissimilarity value to weight the extracted feature at each target position.…”
Section: Related Workmentioning
confidence: 99%