Autonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing

TitleAutonomous Stereo Camera Parameter Estimation for Outdoor Visual Servoing
Publication TypeConference Paper
Year of Publication2007
AuthorsZiraknejad, N., S. Tafazoli, and P. D. Lawrence
Conference NameMachine Learning for Signal Processing, 2007 IEEE Workshop on
Pagination157 -162
Date Publishedaug.
Keywords2D image coordinates, autonomous process, autonomous stereo camera parameter estimation, cameras, data collection process, heavy-duty stereo camera, iterative least-squares parameter estimation algorithm, iterative methods, least squares approximations, manipulators, outdoor 3DOF robotic manipulator, outdoor visual servoing, robot vision, sensor calibration, stereo image processing, target point

In the majority of vision applications, sensor calibration is a prerequisite to proper use of the sensor for both measurement and control. The objective in camera calibration is to estimate a set of parameters to construct a mapping between the 3D position of a target point and its 2D image coordinates. In this paper an autonomous stereo camera calibration technique with applications in industrial outdoor visual servoing systems is presented. The stereo camera model obtained was used to estimate the pose of the target object during the robot servoing process. The heavy-duty stereo camera rig was installed on the torso of an outdoor 3DOF robotic manipulator. An efficient iterative least- squares parameter estimation algorithm was used to estimate the transformation parameters between the 3D world coordinates of the target object and its 2D image coordinates in the stereo image planes. The stereo camera calibration is entirely an autonomous process as the robot moves the calibration tool within its workspace and the stereo camera model is produced after the data collection process. The stereo cameras are treated as a single unit and a single transformation is obtained for the stereo camera pair in the system. The calibration process is fast, efficient and no human interaction is required during the process.


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