Abstract
A vision based algorithm brings fast segmentation process to a 2D lidar point cloud. The extracted features allow us to set up a segment based scan matcher. This matching is one of the steps for the localization. Features also give semantic information about the environment. The detection of a corner or a door indicates a potential encounter with human beings. Aware of this “danger” area, the robot will be able to adapt its speed and define areas of focus to the vision algorithms. Indeed, vision is known for its heavy computation load. The lidar gives a focus area in the image and will reduce the number of pixels to be analysed.
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Burtin, G., Bonnin, P., Malartre, F. (2017). Vision Based Lidar Segmentation for Scan Matching and Camera Fusion. In: Blanc-Talon, J., Penne, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2017. Lecture Notes in Computer Science(), vol 10617. Springer, Cham. https://doi.org/10.1007/978-3-319-70353-4_53
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DOI: https://doi.org/10.1007/978-3-319-70353-4_53
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