An improved spatial histogram and particle filter face tracking

Abstract

Because uniform division spatial histogram can not finely divide the data in relatively concentrated areas, it can not accurately track human faces. A new face tracking method which combines an improved spatial histogram with particle filter is proposed. In this method, non-uniform division is proposed. Histogram data in relatively concentrated areas can be divided finely, and histogram data in relatively sparse areas can be divided roughly. Simultaneously, a new re-sampling method is proposed in order to solve the "particle degradation" and "particle depletion". If many duplicate particles occur, keep a particle, remove other particles. In order to ensure that the total number of particles is N, particles must be selected randomly in the vicinity of the particles which have a large weight. Experiments show that its tracking performance is very good when target color is similar to the scene color and obstructed partly or completely, or under the complex non-linear, non-Gaussian situations.