Categorization of indoor places using the Kinect sensor

Martinez Mozos, Oscar, Mizutani, Hitoshi, Kurazume, Ryo and Hasegawa, Tsutomu (2012) Categorization of indoor places using the Kinect sensor. Sensors, 12 (5). pp. 6695-6711. ISSN 1424-8220

Full content URL: http://dx.doi.org/10.3390/s120506695

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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
Subjects:H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G760 Machine Learning
Divisions:College of Science > School of Computer Science
ID Code:9403
Deposited On:11 May 2013 12:34

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