| 1. | In the solving of absolute conic images , a novel circular point based method is used . the experiments show that the algorithm is feasible
其中在绝对二次曲线的像的求解中研究了一种使用虚圆点的方法，实验结果表明该算法是行之有效的。 |
| 2. | The essence of affine reconstruction is to compute the infinite homographyo the key to metric reconstruction is identification of the absolute conic image , in the end we give a experiment
最后实验分别给出了仿射重构的结果和欧氏重构的结果。实验表明我们的算法是有效的和可行的。 |
| 3. | Expatiate the substance of projective reconstruction is solving fundamental matrix , substance of affine reconstruction is solving infinite homography or infinite plane and substance of metric reconstruction is solving absolute conic images
阐述了射影重构的实质是求解基本矩阵，仿射重构的实质是求解无穷远平面或无穷远平面单应，欧氏重构的实质是求解绝对二次曲线的像。 |
| 4. | The algorithm of camera ' s self - calibration is always a important research domain . in this paper by taking advantage of parallel lines and orthogonal lines in architecture as usual , we can calculate the absolute conic image and vanishing points
摄像机自标定的线性算法一直是计算机视觉领域的研究热点，本文利用场景中的两两正交三条直线，计算直线的消失点，进而线性计算绝对二次曲线的像。 |
| 5. | By taking advantage of parallel lines and orthogonal lines in architecture , the camera internal parameters , rotation and translation can be recovered from a set of un - calibrated images via computing absolute conic and vanishing points . the euclidean 3d model of architecture ( up to a scale factor ) can be recovered too
利用建筑物中常见的平行直线和正交直线等特点，通过绝对二次曲线和消影点等射影几何量的计算，可以从图象中恢复摄像机的内参数、旋转和平移位置，同时恢复建筑物的三维欧氏几何模型（相差一个尺度因子） 。 |
| 6. | In the first part , depending on three or more images , the main research work are listed as follows : ( l ) using svd decomposition to realize projective reconstruction ; ( 2 ) realizing camera self - calibration by solving kruppa ' s equation ; ( s ) recovering euclidean reconstruction from projective reconstruction . depending on only two images , the main researches are : ( l ) making out infinite plane homography matrix by using scene structure information , then recovering affine reconstruction from projective reconstruction ; ( 2 ) making out the absolute conic images by using scene structure information , and then recovering euclidean reconstruction from projective reconstruction
在第一部分中，针对三幅及三幅以上的图像，主要研究：利用矩阵奇异值分解( svd )实现射影重构，通过求解kruppa方程实现摄像机自标定，由射影重构恢复欧氏重构；针对只有两幅图像的情况，主要研究：利用场景结构信息求解无穷远平面的单应矩阵，由射影重构恢复仿射重构，利用场景结构信息求解绝对二次曲线的像(等价于标定摄像机) ，由仿射重构恢复欧氏重构。 |
| 7. | In 3d space , points on the infinite plane compose the absolute conic , and it contains the interior parameter information of camera . we use photography geometry character of circular point on the absolute conic to calculate camera interior parameter , exterior parameter can be obtained . we can obtain more accurate
在三维摄影空间中,无穷远平面上的点构成了绝对二次曲线,由于二次曲线的像包含了摄像机的内部参数信息,我们利用了圆环点的像在二次曲线上的摄影几何特性,从而确定摄像机的内部参数,进而求取摄像机运动的外部参数。 |
| 8. | We systemically discuss how to uniquely decide an infinite plane homography matrix by using the structure information in scene and how to evaluate a homography matrix which convert affine reconstruction to euclidean reconstruction by solving absolute conic images . we give three constraints of absolute conic images and use these constraints to evaluate absolute conic images and then to rec
系统地讨论了如何利用场景中的结构信息，来唯一地确定无穷远平面的单应矩阵，进而由射影重构恢复仿射重构，以及如何通过绝对二次曲线的像求解将仿射重构变换为欧氏重构的单应矩阵。 |
