{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T05:55:28Z","timestamp":1775109328625,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2012,5,22]],"date-time":"2012-05-22T00:00:00Z","timestamp":1337644800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s120506695","type":"journal-article","created":{"date-parts":[[2012,5,22]],"date-time":"2012-05-22T14:22:46Z","timestamp":1337696566000},"page":"6695-6711","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Categorization of Indoor Places Using the Kinect Sensor"],"prefix":"10.3390","volume":"12","author":[{"given":"Oscar Martinez","family":"Mozos","sequence":"first","affiliation":[{"name":"Faculty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hitoshi","family":"Mizutani","sequence":"additional","affiliation":[{"name":"Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryo","family":"Kurazume","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsutomu","family":"Hasegawa","sequence":"additional","affiliation":[{"name":"Faculty of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Martinez, Mozos O. 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