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|Title:||Scale adaptive region covariance descriptor for visual tracking|
|Authors:||Abu Hassan M.F.|
Tuan Dir T.M.A.
|Publisher:||IOP Conference Series: Materials Science and Engineering|
|Citation:||Abu Hassan, M.F., Pri, A.S., Ahmad, Z., Tuan Dir, T.M.A. Scale adaptive region covariance descriptor for visual tracking (2020) IOP Conference Series: Materials Science and Engineering, 932 (1). DOI: 10.1088/1757-899X/932/1/012090.|
|Abstract:||This paper presents an adaptive approach for scale estimation in a tracking-by detection framework. The proposed method works by learning covariance descriptor based on multi-layer instance search region. Our results show that the proposed approach significantly improves the performance in term of detection rate compared to region covariance descriptor with using a fixed bounding box (single scale). From this work, it is believed that we have constructed a greater solution in choosing best layer for this descriptor, permitting to move forward to the next issues such as fast motion or motion blur for achieving a robust tracking system.|
|Description:||This article index by Scopus|
|Appears in Collections:||Conference Papers|
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