Online self-camera orientation based on laser metrology and computer algorithms

An online self-camera orientation for mobile vision is presented. In this technique, the camera orientation is determined during the vision task. This procedure is carried out by Bezier networks of a laser line. Here, the camera orientation is calibrated when the camera is turned during the vision task. Also, the networks perform the three-dimensional vision. The network structure is built based on the behavior of the line shifting, which is provided by the surface depth. From this structure, the initial calibration and the online self-camera orientation are deduced. The proposed technique avoids calibrated references and physical measurements, which are used in the traditional calibration of camera orientation. Thus, calibration limitations caused by camera orientation modifications are overcome to perform the three-dimensional vision. Therefore, the proposed self-camera orientation improves the accuracy and performance of the mobile vision. It is because online data of calibrated references are not passed to the vision system. This procedure represents a contribution in the field of the calibration of camera orientation. To elucidate this contribution, an evaluation is performed based on the reported methods of self-calibration of camera orientation. Also, the time processing is described.