Accession Number : ADA540662


Title :   A General Purpose Feature Extractor for Light Detection and Ranging Data


Descriptive Note : Journal article


Corporate Author : MICHIGAN UNIV ANN ARBOR COMPUTER SCIENCE AND ENGINEERING DIVISION


Personal Author(s) : Li, Yangming ; Olson, Edwin B


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a540662.pdf


Report Date : 17 Nov 2010


Pagination or Media Count : 21


Abstract : Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe a general purpose feature detector for both 2D and 3D LIDAR data that is applicable to virtually any environment. Our method adapts classic feature detection methods from the image processing literature specifically the multi-scale Kanade-Tomasi corner detector. The resulting method is capable of identifying highly stable and repeatable features at a variety of spatial scales without knowledge of environment, and produces principled uncertainty estimates and corner descriptors at same time. We present results on both software simulation and standard datasets, including the 2D Victoria Park and Intel Research Center datasets, and the 3D MIT DARPA Urban Challenge dataset.


Descriptors :   *COMPUTER VISION , *FEATURE EXTRACTION , *OPTICAL RADAR , ROBOTICS , OPTIMIZATION , GRAPHS , ESTIMATES , THREE DIMENSIONAL , MAPPING , UNCERTAINTY , REPRINTS , COMPUTERIZED SIMULATION , TWO DIMENSIONAL


Subject Categories : Cybernetics
      Optical Detection and Detectors


Distribution Statement : APPROVED FOR PUBLIC RELEASE