Open AccessVisual tracking using multi-layer appearance approach
Author(s) -
Mohd Fauzi Abu Hassan,
Azurahisham Sah Pri,
Zakiah Ahmad,
Tengku Mohd Azahar Tuan Dir
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2107/1/012007
Subject(s) - clutter , tracking (education) , artificial intelligence , minimum bounding box , computer science , bounding overwatch , computer vision , covariance , layer (electronics) , pixel , eye tracking , pattern recognition (psychology) , image (mathematics) , mathematics , statistics , psychology , telecommunications , pedagogy , radar , chemistry , organic chemistry
This paper investigated single target tracking of arbitrary objects. Tracking is a difficult problem due to a variety of challenges such as scale variation, motion, background clutter, illumination etc. To achieve better tracking performance under these severe conditions, this paper proposed covariance descriptor based on multi-layer instance search region. Our results show that the proposed approach significantly improves the performance in term of centre location error (in pixels) compared to covariance descriptor with using a fixed bounding box. From this work, it is believed that we have constructed a great solution in choosing best layer for this descriptor. This will be addressed in the next future work such as consider target motion during tracking.