MULTI-KERNEL OBJECT TRACKING (WedAmOR7)

Author(s) : Fatih Porikli (Mitsubishi Electric Research Labs, United States of America) Oncel Tuzel (Mitsubishi Electric Research Labs, United States of America)

Abstract : In this paper, we present an object detection and tracking algorithm for low-frame-rate applications. We extend the standard mean-shift technique such that it is not limited within a single kernel but uses multiple kernels centered around high motion areas obtained by change detection. We also improve the convergence properties of the mean-shift by integrating two additional likelihood terms. Our simulations prove the effectiveness of the proposed method.

Menu