Object tracking in low-frame-rate video
作者： Fatih Porikli , Oncel Tuzel , None
DOI: 10.1117/12.587907
关键词:
摘要: 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. also improve convergence properties of mean-shift integrating two additional likelihood terms. Our simulations prove effectiveness the proposed method.
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