Real Time Mean Shift Tracking Method Based on Human vision Non-uniform Sampling
基于人眼视觉非均匀特性的实时Mean Shift跟踪方法(英文)

Because large quantity information needs to be dealt during imaging processing, the proposed method use human vision non-uniform sample model, called log-polar coordinate model, to compress quantity and increase calculating speed. Invariant feature of image rotation, scaling and gray scale can be gotten by log-polar coordinates transform, so it is a robust approach for tracking Non-rigid deformation of target. Tracking methods using centroid or corner feature maybe bring matching point drift; and in order to supress matching point drift Mean Shift tracking method based on target intensity character was adopt. Mean Shift method used Gauss kernel function was optimized to accelerate calculating speed. The results show that the effectiveness and stability of the proposed approach for supressing matching point drift.