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Título: | High-speed event camera tracking |
Autor: | Chamorro Hernández, William Oswaldo CSIC ORCID; Andrade-Cetto, Juan CSIC ORCID ; Solà, Joan CSIC | Palabras clave: | High speed tracking Event cameras Slam Kalman filter |
Fecha de publicación: | 7-sep-2020 | Citación: | 31st British Machine Vision Conference (2020) | Resumen: | 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 25.8g, at a throughput of 10kHz, 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. | Descripción: | Trabajo presentado en la 31st British Machine Vision Conference, celebrada online del 7 al 10 de septiembre de 2020 | Versión del editor: | https://www.bmvc2020-conference.com/conference/papers/paper_0366.html | URI: | http://hdl.handle.net/10261/235063 |
Aparece en las colecciones: | (IRII) Comunicaciones congresos |
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Fichero | Descripción | Tamaño | Formato | |
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0366.pdf | 9,98 MB | Adobe PDF | Visualizar/Abrir |
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