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Unsupervised feature learning for 3D scene labeling
2014
2014 IEEE International Conference on Robotics and Automation (ICRA)
This paper presents an approach for labeling objects in 3D scenes. We introduce HMP3D, a hierarchical sparse coding technique for learning features from 3D point cloud data. HMP3D classifiers are trained using a synthetic dataset of virtual scenes generated using CAD models from an online database. Our scene labeling system combines features learned from raw RGB-D images and 3D point clouds directly, without any hand-designed features, to assign an object label to every 3D point in the scene.
doi:10.1109/icra.2014.6907298
dblp:conf/icra/LaiBF14
fatcat:vy42aejsnncblmgb4flgyghfki