Moving human detection and recognition in videos using adaptive method and support vector machine

This paper presents a robust adaptive moving human detection and recognition method in videos. The human detection method consists of modified moving average background model with supportive secondary model and an adaptive threshold selection model based on Gaussian distribution. The moving average background model is used for background modeling and the background subtraction system is used to provide foreground image through difference image between current image and background model. The adaptive threshold method is used to simultaneously update the system to environment changes. The modified human model consists of five parts with robust features to facilitate human recognition process. For recognition purpose Support Vector Machine has been used as classifier. Experimental results show the effectiveness of proposed system.