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Proceedings Paper

3D object detection from roadside data using laser scanners
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Paper Abstract

The detection of objects on a given road path by vehicles equipped with range measurement devices is important to many civilian and military applications such as obstacle avoidance in autonomous navigation systems. In this thesis, we develop a method to detect objects of a specific size lying on a road using an acquisition vehicle equipped with forward looking Light Detection And Range (LiDAR) sensors and inertial navigation system. We use GPS data to accurately place the LiDAR points in a world map, extract point cloud clusters protruding from the road, and detect objects of interest using weighted random forest trees. We show that our proposed method is effective in identifying objects for several road datasets collected with various object locations and vehicle speeds.

Paper Details

Date Published: 27 January 2011
PDF: 18 pages
Proc. SPIE 7864, Three-Dimensional Imaging, Interaction, and Measurement, 78640V (27 January 2011); doi: 10.1117/12.872620
Show Author Affiliations
Jimmy Tang, Univ. of California, Berkeley (United States)
Avideh Zakhor, Univ. of California, Berkeley (United States)


Published in SPIE Proceedings Vol. 7864:
Three-Dimensional Imaging, Interaction, and Measurement
J. Angelo Beraldin; Ian E. McDowall; Atilla M. Baskurt; Margaret Dolinsky; Geraldine S. Cheok; Michael B. McCarthy; Ulrich Neuschaefer-Rube, Editor(s)

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