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In this paper, we optimize the placement of a camera in simulation in order to achieve a high success rate for a pose estimation problem. This is achieved by simulating 2D images from a stereo camera in a virtual scene. The stereo images are then used to generate 3D point clouds based on two different methods, namely a single shot stereo matching approach and a multi shot approach using phase shift patterns. After a point cloud is generated, we use a RANSAC-based pose estimation algorithm, which relies on feature matching of local 3D

Simulation-based Optimization of Camera Placement in the Context of Industrial Pose Estimation