Object Tracking in Image Sequences using Point Features

Abstract

This paper presents an object tracking technique based on the Bayesian Multiple Hypothesis Tracking (MHT) approach. Two algorithms, both based on the MHT technique are combined to generate an object tracker. The first MHT algorithm is employed for contour segmentation (based on an edge map). The second MHT algorithm is used in the temporal tracking of a selected object from the initial frame. An object is represented by key feature points that are extracted from it. The key points (mostly corner points) are detected using information obtained from the edge map. These key points are then tracked through the sequence. To confirm the correctness of the tracked key points, the location of the key points on the trajectory are verified against the segmented object identified in each frame. The results show that the tracker proposed can successfully track simple identifiable objects through an image sequence