Clustering based object feature matching for multi-camera system

멀티 카메라 연동을 위한 군집화 기반의 객체 특징 정합

We propose a clustering based object feature matching for identification of same object in multi-camera system. The method is focused on ease to system initialization and extension. Clustering is used to estimate parameters of Gaussian mixture models of objects. A similarity measure between models are determined by Kullback-Leibler divergence. This method can be applied to occlusion problem in tracking.