In this paper, we detail a complete software architecture of a key task that an intelligent vehicle has to deal with: frontal object perception. This task is solved by processing raw data of a radar and a mono-camera to detect and track moving objects. Data sets obtained from highways, country roads and urban areas were used to test the proposed method. Several experiments were conducted to show that the proposed method obtains a better environment representation, i.e., reduces the false alarms and missed detections from individual sensor evidence.
Frontal object perception using radar and mono-vision
2012 IEEE Intelligent Vehicles Symposium ; 159-164
01.06.2012
1305362 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Frontal Object Perception Using Radar and Mono-Vision
British Library Conference Proceedings | 2012
|FUSION AT DETECTION LEVEL FOR FRONTAL OBJECT PERCEPTION
British Library Conference Proceedings | 2014
|Mono-Vision Based Moving Object Detection in Complex Traffic Scenes
British Library Conference Proceedings | 2017
|