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The ArosDyn Project: Robust Analysis of Dynamic Scenes

Abstract : The ArosDyn project aims to develop embedded software for robust analysis of dynamic scenes in urban traffic environments, in order to estimate and predict collision risks during car driving. The on-board telemetric sensors (lidars) and visual sensors (stereo camera) are used to monitor the environment around the car. The algorithms make use of Bayesian fusion of heterogenous sensor data. The key objective is to process sensor data for robust detection and tracking of multiple moving objects for estimating and predicting collision risks in real time, in order to help avoid potentially dangerous situations.
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Contributor : Mathias Perrollaz <>
Submitted on : Friday, December 10, 2010 - 7:00:11 AM
Last modification on : Thursday, November 19, 2020 - 1:00:24 PM
Long-term archiving on: : Friday, March 11, 2011 - 2:34:15 AM


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  • HAL Id : inria-00539999, version 1



Igor Paromtchik, Christian Laugier, Mathias Perrollaz, Yong Mao, Amaury Negre, et al.. The ArosDyn Project: Robust Analysis of Dynamic Scenes. International Conference on Control, Automation, Robotics and Vision, Dec 2010, Singapour, Singapore. ⟨inria-00539999⟩



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