self-calibration, tracking, epipolar geometry

Camera is one of the most important sensors in robotic applications. Calibrated camerasprovide more information than the uncalibrated ones. Intrinsic parameters of acamera can deteriorate due to mechanical and thermal changes in environment. Thereforeself-calibration is required for robotic operations. Since self-calibration does notrequire any known template objects in the process, it is more flexible and extractinga few fixed points between calibration images is enough for self-calibration. Wepropose a new method for simpler and more accurate self-calibration method by incorporatingsome of the extrinsic parameters of camera along with some assumptionswhich are true for present day cameras. Moreover, we have included a basic point detection,tracking and association approach for the task. Proposed method is tested andcompared with another self calibration method using synthetic data, a mobile robotwith a camera in V-REP simulation environment and physical implementation witharticulated robot arm. The results indicate the eectiveness of the new approach withrespect to other self-calibration approaches for planer motion of the camera.