High-speed event camera tracking

Document typeConference report
Defense date2020
Rights accessOpen Access
European Commission's projectGAUSS - Galileo-EGNOS as an Asset for UTM Safety and Security (EC-H2020-776293)
Abstract
Event cameras are bioinspired sensors with reaction times in the order of microseconds. This property makes them appealing for use in highly-dynamic computer vision applications. In this work, we explore the limits of this sensing technology and present an ultra-fast tracking algorithm able to estimate six-degree-of-freedom motion with dynamics over 25.8 g, at a throughput of 10 kHz, processing over a million events per second. Our method is capable of tracking either camera motion or the motion of an object in front of it, using an error-state Kalman filter formulated in a Lie-theoretic sense. The method includes a robust mechanism for the matching of events with projected line segments with very fast outlier rejection. Meticulous treatment of sparse matrices is applied to achieve real-time performance. Different motion models of varying complexity are considered for the sake of comparison and performance analysis.
CitationChamorro, W.; Andrade-Cetto, J.; Solá, J. High-speed event camera tracking. A: British Machine Vision Conference. "Proceedings of the The 31st British Machine Vision Virtual Conference". 2020, p. 1-12.
Publisher versionhttps://www.bmvc2020-conference.com/assets/papers/0366.pdf
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