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Arakawa Kaoru
Department Undergraduate School , School of Interdisciplinary Mathematical Sciences Position Professor |
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| Language | English |
| Publication Date | 2020/12 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Correlation filter-based visual tracking using confidence map and adaptive model |
| Contribution Type | Co-authored (other than first author) |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Journal Type | Another Country |
| Publisher | IEICE |
| Volume, Issue, Page | E103A(12),pp.1512-1519 |
| Total page number | 8 |
| Authorship | Corresponding author |
| Author and coauthor | Z. Tang, K. Arakawa |
| Details | Recently, visual trackers based on the framework of kernelized correlation filter (KCF) achieve the robustness and accuracy results. These trackers need to learn information on the object from each frame, thus the state change of the object affects the tracking performances. In order to deal with the state change, we propose a novel KCF tracker using the filter response map, namely a confidence map, and adaptive model. |