Title :
Tracking both pose and status of a traffic light via an Interacting Multiple Model filter
Author :
Trehard, Guillaume ; Pollard, Evangeline ; Bradai, Benazouz ; Nashashibi, Fawzi
Author_Institution :
IMARA Team, INRIA Rocquencourt, Le Chesnay, France
Abstract :
Either for driver assistance systems or autonomous vehicles, detecting traffic lights (status and pose) is required when Intelligent Transport Systems go downtown. As detection algorithms could still have some misclassification on the traffic light status, this paper proposes a solution to nearly avoid this problem. An Interacting Multiple Model filter is used to track both the position and the status of a traffic light through the time and to increase traffic light recognition performances for automation purpose.
Keywords :
driver information systems; filtering theory; image classification; intelligent transportation systems; object detection; object tracking; road traffic; automation purpose; autonomous vehicles; detection algorithms; driver assistance systems; intelligent transport systems; interacting multiple model filter; position tracking; traffic light pose tracking; traffic light recognition performances; traffic light status misclassification; traffic lights detection; Cameras; Computational modeling; Hidden Markov models; Mathematical model; Noise; Switches; Vehicles;
Conference_Titel :
Information Fusion (FUSION), 2014 17th International Conference on
Conference_Location :
Salamanca