Categorization of indoor places by combining local binary pattern histograms of range and reflectance data from laser range finders

Martinez Mozos, Oscar and Mizutani, Hitoshi and Jung, Hojung and Kurazume, Ryo and Hasegawa, Tsutomu (2013) Categorization of indoor places by combining local binary pattern histograms of range and reflectance data from laser range finders. Advanced Robotics, 27 (18). pp. 1455-1464. ISSN 0169-1864

Full content URL: http://dx.doi.org/10.1080/01691864.2013.839091

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Abstract

This paper presents an approach to categorize typical places in indoor environments using 3D scans provided by a laser range finder. Examples of such places are offices, laboratories, or kitchens. In our method, we combine the range and reflectance data from the laser scan for the final categorization of places. Range and reflectance images are transformed into histograms of local binary patterns and combined into a single feature vector. This vector is later classified using support vector machines. The results of the presented experiments demonstrate the capability of our technique to categorize indoor places with high accuracy. We also show that the combination of range and reflectance information improves the final categorization results in comparison with a single modality.

Additional Information:Published online: 15 Oct 2013 See also: The 8th Joint Workshop on Machine Perception and Robotics (MPR2012), Kyushu University, Fukuoka, Japan, 16 - 17 October 2012,
Keywords:mobile robotics, place categorization, place recognition, semantic mapping, semantic labeling
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G760 Machine Learning
H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
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ID Code:12385
Deposited On:17 Oct 2013 14:35

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