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PanoraMIS: An ultra-wide field of view image dataset for vision-based robot-motion estimation

Houssem-Eddine Benseddik, Fabio Morbidi, Guillaume Caron

Year
2020
Citations
17

Abstract

This article 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.

Keywords

Visual odometryArtificial intelligenceComputer visionComputer scienceCatadioptric systemRobotField (mathematics)Ground truthMotion estimationEngineering

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