A new technique of gait feature extraction based on multi-parameter model

作者：Xue Z J; Wan B K; Liu X H; Ming D^*; Jin S J

来源：Chinese Journal of Biomedical Engineering, 2009, 28(1): 22-26.

• Gait recognition
• Invariant moments
• Skeleton theory
• Support vector machine
• Wavelet decomposition

In order to improve the recognition capability with single model and restrain the impact of noise (walking speed, clothing, illumination, etc) in gait recognition, a novel technique of feature extraction was presented for gait parameters in this paper. This method was based on wavelet decomposition (WD), invariant moments (IM) and skeleton theory (ST) . Body silhouette sequences were extracted and normalized. The sequences were added together and the gait feature image could be achieved. The moment parameters with information of integral model were obtained by using wavelet decomposition and invariant moments. The skeleton was extracted from the gait feature image. Parameters of skeleton involving simplified model were extracted. These parameters, including invariant moments and skeleton, were given to support vector machines (SVM) for gait recognition. This method was applied to Tianjin University Infrared Gait Data-set (TIGD) and achieved recognition rate of 84 ̃ 92 . Results proved that this method would benefit extracting the gait essential feature.

• 出版日期2009
• 单位天津大学