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Sensors 2012, 12(5), 6695-6711; doi:10.3390/s120506695

Categorization of Indoor Places Using the Kinect Sensor

1
Faculty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
2
Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
*
Author to whom correspondence should be addressed.
Received: 14 March 2012 / Revised: 16 May 2012 / Accepted: 16 May 2012 / Published: 22 May 2012
(This article belongs to the Section Physical Sensors)
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Abstract

The categorization of places in indoor environments is an important capability for service robots working and interacting with humans. In this paper we present a method to categorize different areas in indoor environments using a mobile robot equipped with a Kinect camera. Our approach transforms depth and grey scale images taken at each place into histograms of local binary patterns (LBPs) whose dimensionality is further reduced following a uniform criterion. The histograms are then combined into a single feature vector which is categorized using a supervised method. In this work we compare the performance of support vector machines and random forests as supervised classifiers. Finally, we apply our technique to distinguish five different place categories: corridors, laboratories, offices, kitchens, and study rooms. Experimental results show that we can categorize these places with high accuracy using our approach.
Keywords: Kinect sensor; place categorization; service robots Kinect sensor; place categorization; service robots
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Mozos, O.M.; Mizutani, H.; Kurazume, R.; Hasegawa, T. Categorization of Indoor Places Using the Kinect Sensor. Sensors 2012, 12, 6695-6711.

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