Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor
- Authors
- Kim, Han-Ul; Kim, Chang-Su
- Issue Date
- 8월-2017
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Visual tracking; object tracking; bounding box descriptor; discriminative tracker; and tracking with multiple estimators
- Citation
- IEEE TRANSACTIONS ON IMAGE PROCESSING, v.26, no.8, pp.3817 - 3830
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON IMAGE PROCESSING
- Volume
- 26
- Number
- 8
- Start Page
- 3817
- End Page
- 3830
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/82648
- DOI
- 10.1109/TIP.2017.2706064
- ISSN
- 1057-7149
- Abstract
- In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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