@InProceedings{guerbas:icar:2021,
  author    = {Guerbas, Seif and Crombez, Nathan and Caron, Guillaume and Mouaddib, El Mustapha},
  title     = {Direct 3D Model-Based Tracking in Omnidirectional Images Robust to Large Inter-Frame Motion},
  booktitle = {International Conference on Advanced Robotics},
  year      = {2021},
  pages     = {505--510},
  address   = {Ljubljana, Slovenia},
  month     = {December 6-December 10},
  url       = {https://ieeexplore.ieee.org/document/9659324},
  keywords  = {Solid modeling, Three-dimensional displays, Tracking, Urban areas, Transforms, Cameras, Visual servoing},
  doi       = {10.1109/ICAR53236.2021.9659324},
  abstract  = {This paper tackles direct 3D model-based pose tracking. It considers the Photometric Gaussian Mixtures (PGM) transform of omnidirectional images as direct features. The contributions include an adaptation of the pose optimization to omnidirectional cameras and a rethink of the initialization and optimization rules of the PGM extent. These enhancements produce a giant leap in the convergence domain width. Application to images acquired onboard a mobile robot within an urban environment described by a large 3D colored point cloud shows significant robustness to large inter-frame motion, compared to approaches that directly use pixel brightness as direct features.}
}