Learning hierarchical features for automated extraction of road markings from 3-D mobile LiDAR point clouds

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 8, Issue 2, 2015, Pages 709-726

  Yu, Yongtao ^a   Li, Jonathan ^a   Guan, Haiyan ^b   Jia, Fukai ^a   Wang, Cheng ^a  

^a XIAMEN UNIVERSITY   (China)

^b UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Deep learning; mobile light detection and ranging (LiDAR); point cloud; road marking; three dimensional (3 D) extraction

Indexed keywords

CURBS; EXTRACTION; HIGHWAY MARKINGS; OPTICAL RADAR; PRINCIPAL COMPONENT ANALYSIS; ROADS AND STREETS; TRANSPORTATION;

DEEP LEARNING; LIGHT DETECTION AND RANGING; POINT CLOUD; ROAD MARKING; THREEDIMENSIONAL (3-D);

ROAD AND STREET MARKINGS;

IMAGE CLASSIFICATION; LIDAR; PATTERN RECOGNITION; REMOTE SENSING; ROAD; SEGMENTATION;

EID: 85027949298     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2014.2347276     Document Type: Article

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