A learning system for detection and classification of road obstacles, such as vehicles and non-vehicles, is proposed which utilizes information from multiple sensors. An advanced range sensor guides a selection of candidate images provided by the camera for subsequent analysis. A competition based learning algorithm is used to distinguish between representations of different obstacles. High classification accuracy is demonstrated in a realistic variety of driving conditions in the presence of intentional data mislabeling in the two-class setup with state-of-art image descriptors.
Road obstacle classification with attention windows
2010 IEEE Intelligent Vehicles Symposium ; 889-895
01.06.2010
718750 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Road Obstacle Classification with Attention Windows, pp. 889-895
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