Research On Some Problems Of Camera Calibration And Its Applications In Computer Vision

One of the basic tasks of computer vision is recognition and reconstruction of the 3D world by using the 2D image information which was acquired form the camera or any other image ac-quisition devices, and further guiding the machine to cognise the real world. Camera calibration is prerequisite to complete the task above. In the area of traditional camera calibration, researchers carried out extensive work and achieved rich theoretical results and applications, which including building the camera model, design and selection of the camera calibration targets, estimation of the camera pose, extraction of the feature points, build the camera calibration algorithm and achieved variety of specif c applications. Face to the existing problems in the above areas, and under the sup-port of the National Nature Science Foundation of China, this dissertation carried out systematic and in-depth studies. More details are as follows:(1). Automatic extracting the feature points from the chessboard targets. We f rstly used the Wellner adaptive threshold with a Gaussian smoothing operator to f nish the image binarization, and then used the Canny operator to acquire the edge information. In the end, we comprehensively used the multi Radon Transform and sub-image partition methods to f nish the whole automatic corner extraction process based on the route of coarse to f ne. Our work helps to realize a totally automatic camera calibration process, and will improve the efficiency of the camera calibration. We also used an image segmentation and sub-image processing method to reduce the corner location errors, and the results show that we achieved sub-pixel location accuracy. In the f nal, the experiments show that the calibration results which used our corners are equal to the results achieved by the existed mature approaches.(2). A multi-chessboards localization method was mentioned, which was based on the corner classif cation technique. First, we thoroughly analysis the function of the initial parameters belong to the Harris corner detection operator, respectively, and then the criterion of the parameter selec-tion were def ned. We constructed an adaptive rotation scale and size scale binary template, which used for diluting the density of the false corners. We comprehensively used the DBSCAN and FCM clustering algorithm to f nally f nish the false corners f ltering. In the end, the multi-chessboards border was extracted accurately by using the Radon Transform algorithm, respectively. The exper-iments showed that our approach especially suitable for locating multi-chessboards which have a wide and complex background, and also showed that our approach provided an effective way to calibrate a camera just by using a single image.(3). A low-cost and monocular video based 3D head pose tracking and extraction method by using the camera calibration technique was presented. The method can effectively extract the 6 DOF motion parameters which include three translation parameters:Tx, Ty and Tz following the axis X, Y and Z, respectively, and three rotation parameters:y,β, a surrounding the axis X, Y and Z, respectively. In the end, the Extended Kalman Filter (EKF) algorithm was used to solved the problem of data jitter, and some missing-data also could be repaired. We contrasted our method with the motion capture system, the results showed that the method is effective and has the capability of extracting the 3D head pose accurately.(4). Present a new human pupil center location method. We build a three-dimensional geo-metric model of the human eye by using the physiological parameters and 2D eye images. And then, the information of pupil edge was transform form 2D space to 3D space. Edge f tting method was used to acquire the pupil center. In detail, based on the 3D edge points of the pupil, we f rstly calculated the space plane by using the least square algorithm, and then we transform the ellipse f tting into circle f tting which could obviously reduce the demand of the edge information and the complexity of the f tting algorithm. The experiments showed that our method could still accurately extract the center coordinate of the pupil, when the block area arrived at 75%.