Object Tracking by Maximizing Classification Score of Detector Based on Rectangle Features

Abstract

In this paper, we propose a novel classifier-based object tracker. Our tracker is the combination of Rectangle Feature (RF) based detector [17], [18] and optical-flow based tracking method [1]. We show that the gradient of extended RFs can be calculated rapidly by using Integral Image method. The proposed tracker was tested on real video sequences. We applied our tracker for face tracking and car tracking experiments. Our tracker worked over 100fps while maintaining comparable accuracy to RF based detector. Our tracking routine that does not contain image I/O processing can be performed about 500 to 2,500fps with sufficient tracking accuracy.