Gaussian-Process-Based Real-Time Ground Segmentation for Autonomous Land Vehicles

Journal of Intelligent and Robotic Systems: Theory and Applications

Volumn 76, Issue 3-4, 2014, Pages 563-582

  Chen, Tongtong ^a   Dai, Bin ^a   Wang, Ruili ^b   Liu, Daxue ^a  

^a NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

^b MASSEY UNIVERSITY   (New Zealand)

Author keywords

3D point cloud; Autonomous land vehicle; Gaussian process; Ground segmentation

Indexed keywords

AGRICULTURAL ROBOTS; ECONOMIC AND SOCIAL EFFECTS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IMAGE SEGMENTATION; ONE DIMENSIONAL;

3D POINT CLOUD; AUTONOMOUS LAND VEHICLES; GAUSSIAN PROCESSES; NON-STATIONARY COVARIANCE; OBJECT CLASSIFICATION; REAL TIME PERFORMANCE; SEGMENTATION RESULTS; SEGMENTATION TECHNIQUES;

AUTONOMOUS VEHICLES;

EID: 84912047348     PISSN: 09210296     EISSN: 15730409     Source Type: Journal    
DOI: 10.1007/s10846-013-9889-4     Document Type: Article

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