国防科技大学学报
國防科技大學學報
국방과기대학학보
Journal of National University of Defense Technology
2015年
5期
29-34
,共6页
摄像机标定%灭点%椭圆%迭代优化
攝像機標定%滅點%橢圓%迭代優化
섭상궤표정%멸점%타원%질대우화
camera calibration%vanishing points%ellipse%iterative optimization
针对基于灭点的单像自标定方法精度不高的局限性,利用影像中的灭点和椭圆几何约束信息,提出一种迭代优化的单像自标定方法。根据极点-极线关系及其表示的正交性,由影像中的椭圆曲线及其所在平面的灭线确定一组正交共轭灭点对。利用这些正交共轭灭点对建立关于主距和主点的非线性模型,以主距的方差最小作为优化准则,并选用多个位置作为主点的初始值进行多次迭代优化估计,获得主距和主点的最优结果。仿真影像和真实影像实验结果表明,该方法能够有效地实现单像自标定。与基于灭点的摄像机标定方法相比,该方法能够获得更为满意的标定结果。
針對基于滅點的單像自標定方法精度不高的跼限性,利用影像中的滅點和橢圓幾何約束信息,提齣一種迭代優化的單像自標定方法。根據極點-極線關繫及其錶示的正交性,由影像中的橢圓麯線及其所在平麵的滅線確定一組正交共軛滅點對。利用這些正交共軛滅點對建立關于主距和主點的非線性模型,以主距的方差最小作為優化準則,併選用多箇位置作為主點的初始值進行多次迭代優化估計,穫得主距和主點的最優結果。倣真影像和真實影像實驗結果錶明,該方法能夠有效地實現單像自標定。與基于滅點的攝像機標定方法相比,該方法能夠穫得更為滿意的標定結果。
침대기우멸점적단상자표정방법정도불고적국한성,이용영상중적멸점화타원궤하약속신식,제출일충질대우화적단상자표정방법。근거겁점-겁선관계급기표시적정교성,유영상중적타원곡선급기소재평면적멸선학정일조정교공액멸점대。이용저사정교공액멸점대건립관우주거화주점적비선성모형,이주거적방차최소작위우화준칙,병선용다개위치작위주점적초시치진행다차질대우화고계,획득주거화주점적최우결과。방진영상화진실영상실험결과표명,해방법능구유효지실현단상자표정。여기우멸점적섭상궤표정방법상비,해방법능구획득경위만의적표정결과。
The camera calibration from vanishing points is easily distracted by noise in the image,leading to inaccurate results which are often inadmissible for camera calibration.To overcome the limitation,an iterative optimization approach,which makes full use of geometric constraints of vanishing points and ellipse in the image,was presented for self-calibration from single image.According to the pole-polar relationship and the orthogonality represented by it,a set of orthogonal conjugate vanishing point pairs were calculated through using the ellipse curve and the coplanar vanishing line.A nonlinear model of the principle distance and principle point was established on the basis of these vanishing point pairs.Choosing the minimum variance of principle distances as optimization criterion and setting multiple points as the initial values of the principle point,the principle distance and principle point were iteratively optimized and their optimal results were obtained.Simulated results and real data show that the approach can effectively realize camera self-calibration from a single image.Compared with the camera calibration method using vanishing points,the approach achieves more satisfactory calibration results.