Meanshift Tracking with Kalman Filter and Rotation-Invariant Features
Rui Lü, Xin Sheng Huang, Wan Ying Xu, Lu Rong Shen · Applied Mechanics and Materials · 2013
This paper presents an improve Meanshift tracking algorithm based on Kalman filter and Rotation-Invariant Features. Firstly, this paper forecasts the original alternate position using Kalman filter. Secondly, a kind of spatial histogram based on GRA (Gradient Radius Angle, GRA) is introduced, which is a rotation-invariant descriptor combined the information of gradient. At last, this paper searches the scale factor by the normal scale space decomposition technique. Experiments show that the method concerned in this paper has better performances than two improved algorithms.