@inproceedings{fac8d9465e89473d9cf4fdd1712dc56f,
title = "Indoor place categorization using co-occurrences of LBPs in gray and depth images from RGB-D sensors",
abstract = "Indoor place categorization is an important capability for service robots working and interacting in human environments. This paper presents a new place categorization method which uses information about the spatial correlation between the different image modalities provided by RGB-D sensors. Our approach applies co-occurrence histograms of local binary patterns (LBPs) from gray and depth images that correspond to the same indoor scene. The resulting histograms are used as feature vectors in a supervised classifier. Our experimental results show the effectiveness of our method to categorize indoor places using RGB-D cameras.",
author = "Hojung Jung and Mozos, {Oscar Martinez} and Yumi Iwashita and Ryo Kurazume",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 5th International Conference on Emerging Security Technologies, EST 2014 ; Conference date: 10-09-2014 Through 12-09-2014",
year = "2014",
month = dec,
day = "11",
doi = "10.1109/EST.2014.23",
language = "English",
series = "Proceedings - 2014 International Conference on Emerging Security Technologies, EST 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "40--45",
booktitle = "Proceedings - 2014 International Conference on Emerging Security Technologies, EST 2014",
address = "United States",
}