Reducing noise and redundancy in registered range data for planar surface extraction

Swadzba, Agnes, Vollmer, Anna-Lisa, Hanheide, Marc and Wachsmuth, Sven (2008) Reducing noise and redundancy in registered range data for planar surface extraction. In: 19th International Conference on Pattern Recognition, 8-11 December 2008, Tampa, Florida.

Full content URL: http://dx.doi.org/10.1109/ICPR.2008.4761411

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Abstract

This paper presents a new method for detecting
and merging redundant points in registered range data.
Given a global representation from sequences of 3D
points, the points are projected onto a virtual image
plane computed from the intrinsic parameters of the
sensor. Candidates for redundancy are collected per
pixel which then are clustered locally via region growing and replaced by the cluster’s mean value. As data is
provided in a certain manner defined by camera characteristics, this processing step preserves the structural
information of the data. For evaluation, our approach is
compared to two other algorithms. Applied to two dif-
ferent sequences, it is shown that the presented method
gives smooth results within planar regions of the point
clouds by successfully reducing noise and redundancy
and thus improves registered range data.

Additional Information:This paper presents a new method for detecting and merging redundant points in registered range data. Given a global representation from sequences of 3D points, the points are projected onto a virtual image plane computed from the intrinsic parameters of the sensor. Candidates for redundancy are collected per pixel which then are clustered locally via region growing and replaced by the cluster’s mean value. As data is provided in a certain manner defined by camera characteristics, this processing step preserves the structural information of the data. For evaluation, our approach is compared to two other algorithms. Applied to two dif- ferent sequences, it is shown that the presented method gives smooth results within planar regions of the point clouds by successfully reducing noise and redundancy and thus improves registered range data.
Keywords:Robotics, Human-robot interaction
Subjects:H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:6936
Deposited On:29 Dec 2012 16:20

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