Tracking in clutter based on Mean Shift embedded particle filter
Lin Liu Zheng, Quan Liu · 2010
in this paper, we present a new Mean Shift embedded particle filter for visual tracking. Two kinds of Mean Shifts are used. The pixel based Mean Shift is employed to optimize each particle independently and locally. Then the particle based Mean Shift is employed to optimize all the particles dependently. This algorithm is used to track objects in the cluttered environment. The experiments show that the method performs robust in complex situation.