A Benchmark for Full Rotation Head Tracking
Yulin Li, Bingpeng Ma, Hong Lei Chong, Xilin Chen · 2018
This paper introduces a new benchmark for 360-degree rotation head tracking, named Full Rotation Head Tracking (FRHT). The benchmark consists of 50 color sequences containing diverse human activities with complicated head motions. Specially, FRHT covers the most challenges of head tracking and focuses on the appearance variations of heads during the 360-degree rotation. It also pays attention to the clutters from the heads of nearby people. Further, we propose a baseline tracker. It guides a selective adaption updating by verifying strategies, thus alleviates error accumulation. Extensive experiments validate the advantages of FRHT in head rotation and similar object clutter.