TY - JOUR
T1 - Fukuoka datasets for place categorization
AU - Martinez Mozos, Oscar
AU - Nakashima, Kazuto
AU - Jung, Hojung
AU - Iwashita, Yumi
AU - Kurazume, Ryo
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been funded by the Japanese JSPS KAKENHI (grant number JP26249029), by the Spanish DGT (grant number SPIP2017-02286), by the Spanish Fundacion Seneca (grant number 20041/GERM/16), by the Spanish Ramon y Cajal program (grant number RYC-2014-15029), and by Campus Mare Nostrum (UM-UPCT).
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This paper presents several multi-modal 3D datasets for the problem of categorization of places. In this problem. a robotic agent should decide on the type of place/environment where it is located (residential area, forest, etc.) using information gathered by its sensors. In addition to the 3D depth information, the datasets include additional modalities such as RGB or reflectance images. The observations were taken in different indoor and outdoor environments in Fukuoka city, Japan. Outdoor place categories include forests, urban areas, indoor parking, outdoor parking, coastal areas, and residential areas. Indoor place categories include corridors, offices, study rooms, kitchens, laboratories, and toilets. The datasets are available to download at http://robotics.ait.kyushu-u.ac.jp/kyushu_datasets.
AB - This paper presents several multi-modal 3D datasets for the problem of categorization of places. In this problem. a robotic agent should decide on the type of place/environment where it is located (residential area, forest, etc.) using information gathered by its sensors. In addition to the 3D depth information, the datasets include additional modalities such as RGB or reflectance images. The observations were taken in different indoor and outdoor environments in Fukuoka city, Japan. Outdoor place categories include forests, urban areas, indoor parking, outdoor parking, coastal areas, and residential areas. Indoor place categories include corridors, offices, study rooms, kitchens, laboratories, and toilets. The datasets are available to download at http://robotics.ait.kyushu-u.ac.jp/kyushu_datasets.
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U2 - 10.1177/0278364919835603
DO - 10.1177/0278364919835603
M3 - Article
AN - SCOPUS:85063351834
VL - 38
SP - 507
EP - 517
JO - International Journal of Robotics Research
JF - International Journal of Robotics Research
SN - 0278-3649
IS - 5
ER -