Tracking Human Movements in Large View Cases
Amrata Patil, Meenakshi Patil · 2018
Object tracking is an important task in the field of computer vision. In which the camera tracking have become a common requirement in today's society. The inexpensive video camera and the high quality lens generate a great interest in the object tracking field. Generally, it is not easy to track human behavior in an environment with a large view. So the project aims to solve the big problems which are associated with the large view camera system to track the people in the large area which is single targets in nonlinear motion, handle occlusion & to reduce the processing time. In this paper a new algorithm is used to solve the problems which are by using a GbLN-BCO & model based particle filter. The proposed algorithm is tested on the several set of video data. The accuracy of the tracking perform is greater than the previous techniques i.e. unscented Kalman filter & Parzen Particle Filter.