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Summary: FLIRT Interest Regions for 2D Range Data
Gian Diego Tipaldi and Kai O. Arras
Abstract-- Local image features are used for a wide range
of applications in computer vision and range imaging. While
there is a great variety of detector-descriptor combinations for
image data and 3D point clouds, there is no general method
readily available for 2D range data. For this reason, the paper
first proposes a set of benchmark experiments on detector re-
peatability and descriptor matching performance using known
indoor and outdoor data sets for robot navigation. Secondly,
the paper introduces FLIRT that stands for Fast Laser Interest
Region Transform, a multi-scale interest region operator for 2D
range data. FLIRT combines the best detector with the best
descriptor, experimentally found in a comprehensive analysis
of alternative detector and descriptor approaches. The analysis
yields repeatability and matching performance results similar to
the values found for features in the computer vision literature,
encouraging a wide range of applications of FLIRT on 2D
range data. We finally show how FLIRT can be used in
conjunction with RANSAC to address the loop closing/global
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