Multi-object tracking using TLD framework

Abstract

This paper demonstrates the framework for multi-object tracking using TLD background. We examine long-term tracking of object in a video stream. The object is characterized by its location and extent in the video frame. In every next frame, the aim is to calculate the location and extent of object or indicate that object is not present. There are different algorithms which perceive the object in real-time. This system proposes a model which uses modified template matching algorithm based on SURF algorithm and squared difference error method. The template matching is done based on comparison of image features. SURF algorithm of template matching is based on feature point detection from images whereas as the template matching is based on pixel feature comparison. We develop a novel method of tracking based upon template tracking algorithm which crops the region of interest(ROI) from the selected live object from a video stream from trained object database. Matching feature is found by applying principle component analysis.