DocumentCode :
1939558
Title :
Reliable pedestrian recognition combining high-definition LIDAR and vision data
Author :
Kidono, Kiyosumi ; Naito, Takashi ; Miura, Jun
Author_Institution :
Road Environ. Perception Lab., Toyota Central R&D Labs., Inc., Nagakute, Japan
fYear :
2012
fDate :
16-19 Sept. 2012
Firstpage :
1783
Lastpage :
1788
Abstract :
Pedestrian recognition is one of the key technologies for advanced driver assistance systems and autonomous driving systems. The present paper proposes a fusion system for reliable pedestrian recognition using high-definition LIDAR and a vision sensor to achieve high performance under various conditions. Pedestrian candidates are extracted from two sensors in parallel by support vector machine-based classifiers. In particular, the region of interest in the image processing is set based on information about objects derived from the LIDAR processing in order to reduce false positives as well as the computational burden. All candidates are integrated by their likelihood, as calculated from their classification scores, using multiple thresholds according to the detection condition of the target in two sensors. A quantitative evaluation in a road environment confirms the effectiveness of the proposed system.
Keywords :
image recognition; image sensors; optical radar; pattern classification; pedestrians; radar computing; radar imaging; sensor fusion; support vector machines; advanced driver assistance system; autonomous driving system; fusion system; high-definition LIDAR; image processing; multiple threshold; pedestrian recognition reliability; support vector machine-based classifier; vision data sensor extraction; Cameras; Feature extraction; Laser radar; Reliability; Support vector machines; 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.2012.6338657
Filename :
6338657
Link To Document :
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