Name
Abstract | ||
|---|---|---|
AbstractThis 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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1177/0278364919835603 | Periodicals |
Keywords | Field | DocType |
place categorization, outdoor scenario, indoor scenario, 3D data, multi-modal data, mobile robotics, labeling, dataset | Categorization,Control engineering,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
38 | 5 | 0278-3649 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Óscar Martínez Mozos | 1 | 429 | 25.82 |
| Kazuto Nakashima | 2 | 1 | 3.14 |
| Hojung Jung | 3 | 8 | 2.51 |
| Yumi Iwashita | 4 | 212 | 23.59 |
| Ryo Kurazume | 5 | 622 | 74.18 |