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Title : REGISTRATION OF LIDAR POINT CLOUDS USING IMAGE FEATURES
Company : Texas A&M University
File Name : Majji.pdf
Size : 854237
Type : application/pdf
Date : 21-Jul-2010
Downloads : 9

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Featured Paper by

Manoranjan Majji, Brein Flewelling, Brent Macomber, John L. Junkins, Anup B. Katake, Hyochung Bang

An optimal linear translation and attitude estimation (OLTAE) algorithm is proposed to register 3dimensional point clouds based on the image features associated with the individual data sets. In LIDAR applications, such images are created by projecting the point cloud data on to an image plane. Physically, this image is the return light intensity observed by the LIDAR imager that is usually available to the analyst for post processing. Associated image features are extracted from the corresponding images by utilizing the recent advances in computational vision and image processing. Features thus obtained have unique descriptors that automate the matching process and ease the solution of the so-called correspondence problem.
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