Real-time resource allocation for tracking systems

(2017) Real-time resource allocation for tracking systems. .

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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 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 pixel boxes in the image. We prove that Parti- Max 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)
Depositing User: Symplectic Admin
Date Deposited: 24 Aug 2017 09:01
Last Modified: 10 Jan 2019 22:11
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