DocumentCode :
1944240
Title :
Semantic-based road environment recognition in mixed traffic for intelligent vehicles and advanced driver assistance systems
Author :
Guo, Chunzhao ; Mita, Seiichi
Author_Institution :
Toyota Technol. Inst., Nagoya, Japan
fYear :
2012
fDate :
16-19 Sept. 2012
Firstpage :
444
Lastpage :
450
Abstract :
Comprehensive situational awareness is paramount to the effectiveness of higher-level functions of the intelligent vehicles and advanced driver assistance systems (ADASs). This paper addresses a hierarchical vision system designed for recognizing a number of objects of interest in mixed traffic, in which, the host vehicle have to drive inside the road boundary and interact with other road users. In the proposed system, the semantic knowledge of the scene is utilized to construct a graph. S tereo vision associated with the semantic graph is employed to seek the drivable road boundary in a Hidden Markov Model (HMM). The results are then used as the road contextual information for the following procedure, in which, particular objects of interest, including vehicles, pedestrians, motorcycles and bicycles, are recognized by using a multi-class object detector. Experimental results in various typical but challenging scenarios show the effectiveness of the proposed system.
Keywords :
computer vision; driver information systems; graph theory; hidden Markov models; object detection; object recognition; road traffic; stereo image processing; ADAS; HMM; advanced driver assistance systems; bicycles; hidden Markov model; hierarchical vision system; host vehicle; intelligent vehicles; mixed traffic; motorcycles; multiclass object detector; pedestrians; road boundary; road contextual information; scene semantic knowledge; semantic graph; semantic-based road environment recognition; situational awareness; stereo vision; Cameras; Deformable models; Estimation; Hidden Markov models; Roads; Semantics; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
Conference_Location :
Anchorage, AK
ISSN :
2153-0009
Print_ISBN :
978-1-4673-3064-0
Electronic_ISBN :
2153-0009
Type :
conf
DOI :
10.1109/ITSC.2012.6338871
Filename :
6338871
Link To Document :
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