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arXiv · 2010.03024

Real-Time Resource Allocation for Tracking Systems

Yash Satsangi·Shimon Whiteson·Frans A. Oliehoek·Henri Bouma
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Abstract

Automated tracking is key to many computer vision applications. However, many tracking systems struggle to perform in real-time due to the high computational cost of detecting people, especially in ultra high resolution images. We propose a new algorithm called \emph{PartiMax} that greatly reduces this cost by applying the person detector only to the relevant parts of the image. PartiMax exploits information in the particle filter to select $k$ of the $n$ candidate \emph{pixel boxes} in the image. We prove that PartiMax is guaranteed to make a near-optimal selection with error bounds that are independent of the problem size. Furthermore, empirical results on a real-life dataset show that our system runs in real-time by processing only 10\% of the pixel boxes in the image while still retaining 80\% of the original tracking performance achieved when processing all pixel boxes.

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Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Henri Bouma. 2020-09-21. Real-Time Resource Allocation for Tracking Systems. https://arxiv.org/abs/2010.03024

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