Multi-modal panoramic 3D outdoor datasets for place categorization
We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area, urban area and indoor/outdoor parking lot. The first dataset consists of 650 static panoramic scans of dense (9,000,000 points) 3D color and reflectance point clouds obtained using a FARO laser scanner with synchronized color images. The second dataset consists of 34,200 real-time panoramic scans of sparse (70,000 points) 3D reflectance point clouds obtained using a Velodyne laser scanner while driving a car. The datasets were obtained in the city of Fukuoka, Japan and are publicly available in [1], [2]. In addition, we compare several appr...
| Authors | Hojung Jung, Yuki Oto, Oscar M. Mozos et al. |
|---|---|
| Primary category | cs.RO |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
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