Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Estimating Intrinsic Camera Parameters from the Fundamental Matrix Using an Evolutionary Approach | EURASIP Journal on Applied Signal Processing 2004 8 1113-1124 2004 Hindawi Publishing Corporation Estimating Intrinsic Camera Parameters from the Fundamental Matrix Using an Evolutionary Approach Anthony Whitehead School of Computer Science Carleton University Ottawa ON Canada K1S 5B6 Email awhitehe@ Gerhard Roth National Research Council of Canada Ottawa ON Canada K1A 0R6 Email Received 30 June 2002 Revised 21 October 2003 Recommended for Publication by Stefano Cagnoni Calibration is the process of computing the intrinsic internal camera parameters from a series of images. Normally calibration is done by placing predefined targets in the scene or by having special camera motions such as rotations. If these two restrictions do not hold then this calibration process is called autocalibration because it is done automatically without user intervention. Using autocalibration it is possible to create 3D reconstructions from a sequence of uncalibrated images without having to rely on a formal camera calibration process. The fundamental matrix describes the epipolar geometry between a pair of images and it can be calculated directly from 2D image correspondences. We show that autocalibration from a set of fundamental matrices can simply be transformed into a global minimization problem utilizing a cost function. We use a stochastic optimization approach taken from the field of evolutionary computing to solve this problem. A number of experiments are performed on published and standardized data sets that show the effectiveness of the approach. The basic assumption of this method is that the internal intrinsic camera parameters remain constant throughout the image sequence that is the images are taken from the same camera without varying such quantities as the focal length. We show that for the autocalibration of the focal length and aspect ratio the evolutionary method achieves results comparable to published methods but is simpler to .
