A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information

Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm.