@Article{benseddik:ijrr:2020,
  author    = {Benseddik, Hossem, Eddine and Morbidi, Fabio and Caron, Guillaume},
  title     = {PanoraMIS: An Ultra-wide Field of View Image Dataset for Vision-based Robot-Motion Estimation},
  journal   = {The International Journal of Robotics Research},
  year      = {2020},
  volume    = {39},
  number    = {9},
  pages     = {1037--1051},
  month     = {March},
  doi       = {10.1177/0278364920915248},
  url       = {https://hal.archives-ouvertes.fr/hal-02492460/document},
  keywords  = {Panoramic cameras, omnidirectional vision, visual-inertial odometry, image-based localization, autonomous robots},
  abstract  = {This paper presents a new dataset of ultra-wide field of view images with accurate ground truth, called PanoraMIS. The dataset covers a large spectrum of panoramic cameras (catadioptric, twin-fisheye), robotic platforms (wheeled, aerial and industrial robots), and testing environments (indoors and outdoors), and it is well suited to rigorously validate novel image-based robot-motion estimation algorithms, including visual odometry, visual SLAM, and deep learning-based methods. PanoraMIS and the accompanying documentation is publicly available on the Internet for the entire research community.},
  publisher = {Sage Publications Ltd},
  address   = {1 Olivers Yard, 55 City Road, London EC1Y 1SP, England}
}