Real-Time Resource Allocation for Tracking Systems


Satsangi, Yash, Whiteson, Shimon, Oliehoek, Frans A ORCID: 0000-0003-4372-5055 and Bouma, Henri (2017) Real-Time Resource Allocation for Tracking Systems. In: Conference on Uncertainty in Artificial Intelligence.

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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.

Item Type: Conference or Workshop Item (Unspecified)
Additional Information: http://auai.org/uai2017/proceedings/papers/130.pdf
Uncontrolled Keywords: cs.CV, cs.CV
Depositing User: Symplectic Admin
Date Deposited: 24 Aug 2017 09:01
Last Modified: 24 Nov 2023 01:30
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3009113
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