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Paper TuB08.6

Tatoglu, Akin (Stevens Institute of Technology), Pochiraju, Kishore (Stevens Institute of Technology)

Point Cloud Segmentation with LIDAR Reflection Intensity Behavior

Scheduled for presentation during the Regular Session "3D Surface Models, Point Cloud Processing" (TuB08), Tuesday, May 15, 2012, 11:45−12:00, Meeting Room 8 (Wacipi)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on August 20, 2018

Keywords Sensor Networks, Localization

Abstract

Light Detection and Ranging (LIDAR) scans are increasingly being used for 3D map construction and reverse engineering. The utility and benefit of the processed data maybe enhanced if the objects and geometry of the area scanned can be segmented and labeled. In this paper, we present techniques to model the intensity of the laser reflection return from a point during LIDAR scanning to determine diffuse and specular reflection properties of the scanned surface. Using several illumination models, the reflection properties of the surface are characterized by Lambertian diffuse reflection model and Phong, Gaussian and Beckmann specular models. Experimental set up with eight different surfaces with varied textures and glossiness enabled measurement of algorithm performance. Examples of point cloud segmentation with the presented approach are presented.

 

 

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