Position and Posture Estimation of Primitive Shapes Using Deep Learning-Based Object Extraction and Point Cloud-Based Face Extraction
Tatsuya Noguchi, Hiromitsu Fujii · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2020
In this paper, for robot vision as home assistance, a pose estimation method of the generic objects is proposed. The proposed method approximates genetic objects as primitive shapes using a deep learning technique. Furthermore, the surfaces are extracted from normals and curvatures which are calculated by using depth data. Finally, the positions and postures are estimated using pose of surfaces.