Authors:
Troels B. Jørgensen
1
;
Thorbjørn M. Iversen
1
;
Anders P. Lindvig
1
;
Christian Schlette
1
;
Dirk Kraft
1
;
Thiusius R. Savarimuthu
1
;
Jürgen Rossmann
2
and
Norbert Krüger
1
Affiliations:
1
University of Southern Denmark, Denmark
;
2
RWTH Aachen University, Germany
Keyword(s):
Pose Estimation, Simulation, Optimization.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Robotics
;
Shape Representation and Matching
;
Software Engineering
Abstract:
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
descriptors.
The object we pose estimate is a tray containing items to be grasped by a robot. The pose estimation is done
for different positions of the tray and with different item configuration in the tray, in order to determine the
success rate of the pose estimation algorithm for a specific camera placement. Then the camera placement
is varied according to different optimization algorithms in order to maximize the success rate. Finally, we
evaluate the simulation in a real world scene, to determine whether the optimal camera position found in
simulation matches the real scenario.
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