Occluded Human Tracking and Identification Using Image Annotation
Devinder Kumar, Amarjot Singh · International Journal of Image Graphics and Signal Processing · 2012
The important task of human tracking can be difficult to implement in real world environment as the videos can involve complex scenes, severe occlusion and even moving background.Tracking individual objects in a cluttered scene is an important aspect of surveillance.In addition, the systems should also avoid misclassification which can lead to inaccurate tracking.This paper makes use of an efficient image annotation for human tracking.According to the literature survey, this is the first paper which proposes the application of the image annotation algorithm towards human tracking.The method divides the video scene into multiple layers assigning each layer to the individual object of interest.Since each layer has been assigned to a specific object in the video sequence: (i) we can track and analyse the movement of each object individually (ii) The method is able to reframe from misclassification as each object has been assigned a respective layer.The error incurred by the system with movement from one frame to another is presented with detailed simulations and is compared with the conventional Horn-Schunck alone.