Coaxials dataset

• Coaxials dataset was created in a research on the semantic segmentation task of automonous mobility robots operating near humans.
• The dataset contains coaxial color (RGB) images and long wavelength infrared (LWIR) images captured with the same optical axis.
• As a notable feature of the dataset, one of the annotated labels is "glass", such as windows, walls, and automatic doors. Glass is transparent in color images but opaque in LWIR images.
• According to our paper, you can detect transparent glass using coaxial RGB and LWIR images.

Images and annotations

• The images was captured with a coaxial camera, FIRplus, manufactured by the ViewPlus Corporation, Japan.

• The dataset contains 17,023 image pairs, which is divided into 8,050 pairs of learning data, 8,373 pairs of evaluation data, and 600 pairs of verification data.

• Nine labels were annotated: glass, pedestrian, road, aisle, tree, bicycle, car, devaluation, and curb.

• The images were captured in eight lighting condition: daytime (clear sky, cloudy, rainy, snowy, indoor), evening, and night.

• Examples of image# Images and annotations

Download dataset

• Coaxials dataset is available on google drive. The file size is about 3 GB.

Citation

• If you use Coaxials dataset in your work, please cite the following paper.

  @PROCEEDINGS{coaxials-2019,
    title = {Simultaneous transparent and non-transparent object segmentation with multispectral scenes},
    author = {Okazawa, Atsuro and Takahata, Tomoyuki and Harada, Tatsuya},
    booktitle = {2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS2019)},
    year = {2019}
  }