Adaptive Multi-feature-fused Tracking Algorithm for People Counting Application
Shulin Zhou · Science Technology and Engineering · 2010
An improved tracking algorithm is presented to solve the problem that traditional algorithm based on mean shift often causes mistakes if there are similar object appears.HSV color histograms and local binary pattern as the observation model are regards.In order to avoid interference during the tracking,the weights of features are modified according to the similarity between target and model.Then we an automated people counting system is build on that basis.Experimental results show that the proposed algorithm can track more accurately after extract moving targets,and access statistics of the scenes with high accuracy and effectiveness.