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Erschienen in:
2015 | OriginalPaper | Buchkapitel
An Improved Spatial Histogram and Particle Filter Face Tracking
verfasst von : Dingli Yang, Yulin Zhang, Rendong Ji, Yazhou Li, Liqun Huangfu, Yudong Yang
Erschienen in: Genetic and Evolutionary Computing
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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.