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Proceedings Paper

Object tracking in low-frame-rate video
Author(s): Fatih Porikli; Oncel Tuzel
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Paper 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.

Paper Details

Date Published: 14 March 2005
PDF: 8 pages
Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); doi: 10.1117/12.587907
Show Author Affiliations
Fatih Porikli, Mitsubishi Electric Research Labs. (United States)
Oncel Tuzel, Mitsubishi Electric Research Labs. (United States)


Published in SPIE Proceedings Vol. 5685:
Image and Video Communications and Processing 2005
Amir Said; John G. Apostolopoulos, Editor(s)

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