VIPose: Real-time Visual-Inertial 6D Object Pose Tracking

@article{Ge2021VIPoseRV,
  title={VIPose: Real-time Visual-Inertial 6D Object Pose Tracking},
  author={Rundong Ge and Giuseppe Loianno},
  journal={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2021},
  pages={4597-4603}
}
  • Rundong GeGiuseppe Loianno
  • Published 27 July 2021
  • Computer Science
  • 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Estimating the 6D pose of objects is beneficial for robotics tasks such as transportation, autonomous navigation, manipulation as well as in scenarios beyond robotics like virtual and augmented reality. With respect to single image pose estimation, pose tracking takes into account the temporal information across multiple frames to overcome possible detection inconsistencies and to improve the pose estimation efficiency. In this work, we introduce a novel Deep Neural Network (DNN) called VIPose… 
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