Object detection and modeling algorithm for automatic visual people counting system

This paper presents object detection and modeling algorithm for automatic visual people counting system to identify individuals from top view images acquired from an overhead surveillance camera. This work proposes Snake algorithm with effective external energy function and a half-circle template initialization for modeling passengers. The experiment result showed that the proposed method could fit the Snake to the head and shoulder boundaries of the passengers effectively. Fitting error of 3.76 pixels per control point was obtained in our experiment. The information is not only useful for verifying humans but also for extracting appearance features to enhance performance of the subsequent tracking algorithm.