平面上散乱数据点的二次曲线拟合

基于代数距离定义目标函数，在6种不同约束条件下得到6条基本二次曲线，最终的拟合二次曲线由6条基本二次曲线系数加权平均产生．用实例对该方法和其他几种方法拟合曲线的误差作了比较，并讨论了基于代数距离目标函数的几何意义．     

Conic reconstruction and correspondence from two views

Conics are widely accepted as one of the most fundamental image features together with points and line segments. The problem of space reconstruction and correspondence of two conics from two views is addressed in this paper. It is shown that there are two independent polynomial conditions on the corresponding pair of conics across two views, given the relative orientation of the two views. These two correspondence conditions are derived algebraically and one of them is shown to be fundamental in establishing the correspondences of conics. A unified closed-form solution is also developed for both projective reconstruction of conics in space from two uncalibrated camera views and metric reconstruction from two calibrated camera views. Experiments are conducted to demonstrate the discriminality of the correspondence conditions and the accuracy and stability of the reconstruction both for simulated and real images     

A geometric approach for the analysis and computation of the intrinsic camera parameters

The authors of this paper adopted the projected characteristics of the absolute conic in terms of the Pascal's theorem to propose an entirely new camera calibration method based on purely geometric thoughts. The use of this theorem in the geometric algebra framework allows us to compute a projective invariant using the conics of only two images which expressed using brackets helps us to set enough equations to solve the calibration problem. The method requires restricted controlled camera movements. Our method is less sensitive to noise as the Kruppa's-equation-based methods. Experiments with simulated and real images confirm that the performance of the algorithm is reliable.     

二维形状的透视不变性认别

在计算机视觉中,二维形状的识别有着十分重要的意义.为了实现二维形状的透视投影 不变性识别,本文推导出了一种共面二次曲线对的透视投影不变量,提出了一种基于椭圆的平 面曲线的透视不变性表示方法,并且给出了用该不变量和不变性表示方法实现二维形状识别 的算法.实验结果证实了该算法的有效性.     

Conics-based stereo,motion estimation,and pose determination

Stereo vision, motion and structure parameter estimation, and pose determination are three important problems in 3-D computer vision. The first step in all of these problems is to choose and to extract primitives and their features in images. In most of the previous work, people usually use edge points or straight line segments as primitives and their local properties as features. Few methods have been presented in the literature using more compact primitives and their global features. This article presents an approach using conics as primitives. For stereo vision, a closed-form solution is provided for both establishing the correspondence of conics in images and the reconstruction of conics in space. With this method, the correspondence is uniquely determined and the reconstruction is global. It is shown that the method can be extended for higher degree (degree3) planar curves.For motion and structure parameter estimation, it is shown that, in general, two sequential images of at least three conics are needed in order to determine the camera motion. A complicated nonlinear system must be solved in this case. In particular, if we are given two images of a pair of coplanar conics, a closed-form solution of camera motion is presented. In a CAD-based vision system, the object models are available, and this makes it possible to recognize 3-D objects and to determine their poses from a single image.For pose determination, it is shown that if there exist two conics on the surface of an object, the object's pose can be determined by an efficient one-dimensional search. In particular, if two conics are coplanar, a closed-form solution of the object's pose is presented.Uniqueness analysis and some experiments with real or synthesized data are presented in this article.     

一类代数空间逼近样条

给定空间不共面的四个有序数据点,可以形成一个四面体。在四面体内,Bernstein-Bézier（B-B）形式定义两类正则实多项式代数曲面片,一类是二次的,一类是三次的。此两类曲面片在四面体内的交集为一条正则曲线段。先固定二次曲面片,并得到其参数形式,然后约简三次曲面片所对应的Bernstein系数,使之为带有三个形状调整的形状因子,其中两个分别代表曲线段端点处的曲率,另外一个作为形状的调整。利用二次曲面的参数形式,由三次曲面片可得到曲线的隐参数约束形式,从而得到曲线的参数形式。对给定的空间点列,利用两个形状因子较容易的拼接出G²-连续的逼近曲线,突破了现行代数曲线生成方法,即空间连续曲线均是通过三角形仿射变换,由B-B形式生成的平面弧拼接而成。     

Model-based recognition of 3D objects from single images

In this work, we treat major problems of object recognition which have received relatively little attention lately. Among them are the loss of depth information in the projection from a 3D object to a single 2D image, and the complexity of finding feature correspondences between images. We use geometric invariants to reduce the complexity of these problems. There are no geometric invariants of a projection from 3D to 2D. However, given certain modeling assumptions about the 3D object, such invariants can be found. The modeling assumptions can be either a particular model or a generic assumption about a class of models. Here, we use such assumptions for single-view recognition. We find algebraic relations between the invariants of a 3D model and those of its 2D image under general projective projection. These relations can be described geometrically as invariant models in a 3D invariant space, illuminated by invariant “light rays,” and projected onto an invariant version of the given image. We apply the method to real images     

Identical Projective Geometric Properties of Central Catadioptric Line Images and Sphere Images with Applications to Calibration

Central catadioptric cameras are imaging devices that use mirrors to enhance the field of view while preserving a single effective viewpoint. Lines and spheres in space are all projected into conics in the central catadioptric image planes, and such conics are called line images and sphere images, respectively. We discovered that there exists an imaginary conic in the central catadioptric image planes, defined as the modified image of the absolute conic (MIAC), and by utilizing the MIAC, the novel identical projective geometric properties of line images and sphere images may be exploited: Each line image or each sphere image is double-contact with the MIAC, which is an analogy of the discovery in pinhole camera that the image of the absolute conic (IAC) is double-contact with sphere images. Note that the IAC also exists in the central catadioptric image plane, but it does not have the double-contact properties with line images or sphere images. This is the main reason to propose the MIAC. From these geometric properties with the MIAC, two linear calibration methods for central catadioptric cameras using sphere images as well as using line images are proposed in the same framework. Note that there are many linear approaches to central catadioptric camera calibration using line images. It seems that to use the properties that line images are tangent to the MIAC only leads to an alternative geometric construction for calibration. However, for sphere images, there are only some nonlinear calibration methods in literature. Therefore, to propose linear methods for sphere images may be the main contribution of this paper. Our new algorithms have been tested in extensive experiments with respect to noise sensitivity.     

空间二次曲线射影重建计算方法研究

利用二次曲线上点和直线的对应以及利用二次曲线光流对二次曲线进行解释,需要寻求多元方程组的最优解,计算过程较为复杂。将空间二次曲线表示为一个空间二次曲面和一个平面的交线,提出了一对对应二次曲线存在两个独立的多项式条件;利用两个二次曲面的基曲线推导出二次曲线重建的两个对应条件,在此基础上,给出了空间二次曲线射影重建的计算方法和计算步骤。实验验证表明该算法实用和可靠。     

点模式匹配

利用不可约四和相对不变量理论提出了几种点模式新算法,它们可分别用来解决相似变换和上具有相同点数的两个点模式的匹配问题,这些算法的基本出发点 待匹配的两个二维占 分别转化成为一个ｎ维空间中的向量,只要对这两个向量中的各元素进行简单的排序就可解决对应的原来点模式的匹配问题,理论分析和仿真实验表明这些算法是有效的。     

共形几何代数--几何代数的新理论和计算框架

共形几何代数是一个新的几何表示和计算工具.作为几何的高级不变量和协变量系统的结合,它为经典几何提供了统一和简洁的齐性代数框架,以及高效的展开、消元和化简算法,从而可以进行极其复杂的符号几何计算,在几何建模与计算方面表现出很大的优势.主要讲述共形几何代数的产生背景和意义,共形几何代数的数学理论和它最有特色的几个部分,包括Grassmann结构、统一几何表示和旋量作用、基本不变量系统和高级不变量系统、新的计算思想、展开和化简技术等.     

Using Galois Ideals for Computing Relative Resolvents

In this paper we show that some ideals which occur in Galois theory are generated by triangular sets of polynomials. This geometric property seems important for the development of symbolic methods in Galois theory. It may and should be exploited in order to obtain more efficient algorithms, and it enables us to present a new algebraic method for computing relative resolvents which works with any polynomial invariant.     

The invariant representations of a quadric cone and a twisted cubic

Up to now, the shortest invariant representation of a quadric has 138 summands and there has been no invariant representation of a twisted cubic in 3D projective space, which limit to some extent the applications of invariants in 3D space. We give a very short invariant representation of a quadric cone, a special quadric, which has only two summands similar to the invariant representation of a planar conic, and give a short invariant representation of a twisted cubic. Then, a completely linear algorithm for generating the parametric equations of a twisted cubic is provided also. Finally, we exemplify some applications of our proposed invariant representations in the fields of computer vision and automated geometric theorem proving.     

Simple LP-type criteria for positively invariant polyhedral sets

Let S be a convex polyhedral set in the state space of a linear dynamical system. A new proof of an algebraic condition for the set S to be positively invariant is given by the dual set of S. The condition obtained in this correspondence can be examined by solving a set of standard LP-type formulas. It is also shown that the conventional algebraic conditions have redundancies in the LP-type formulas. Discrete-time systems as well as continuous-time systems are considered     

Direct least square fitting of ellipses

This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac-b²=1, the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: It is ellipse-specific, so that even bad data will always return an ellipse. It can be solved naturally by a generalized eigensystem. It is extremely robust, efficient, and easy to implement     

共形几何代数与几何不变量的代数运算

几何不变量的使用是计算机视觉和图形学的一个重要手段.发现一个不变量后,如何找到它与其他不变量的关系,是实际应用中的一个重要问题,这种关系的探讨主要依靠在不变量层次上的代数运算.文中介绍了共形几何代数中的基本、高级和有理不变量如何在几何问题中自然出现,它们之间如何进行代数运算,以及如何通过不变量的化简,自然地得到几何条件的充分必要化和几何定理的完全化.几何定理的机器证明作为几何定理完全化的副产品,被发展成几何定理的关系定量化,这种量化的几何还原就是几何定理的自然推广.几何不变量之间的几何关系的计算是这些技术的一个具体应用.     

Algebraic Conditions for Classifying the Positional Relationships Between Two Conics and Their Applications

In many fields of computer science such as computer animation, computer graphics, computer aided geometric design and robotics, it is a common problem to detect the positional relationships of several entities. Based on generalized characteristic polynomials and projective transformations, algebraic conditions are derived for detecting the various positional relationships betweeu two planar conics, namely, outer separation, exterior contact, intersection, interior contact and inclusion. Then the results are applied to detecting the positional relationships between a cylinder (or a cone) and a quadric. The criteria is very effective and easier to use than other known methods.     

A double look at duality

The two forms of duality that are encountered most frequently by the systems theorist-linear duality and convex duality-are examined. Linear duality has a strong algebraic characterization which extends to other structures such as groups and modules. Convex duality, on the other hand, capitalizes so strongly on the vector space structure that the resulting powerful theory (which is typically interpreted geometrically) loses the algebraic flavor of its roots. An algebraic characterization of convex duality is presented that generalizes the standard algebraic characterization of linear duality. This provides a link between the two forms of duality most important for the systems theorist. The algebraic and geometric interpretations together give a double view of duality as used in systems theory     

Circular motion geometry using minimal data

Circular motion or single axis motion is widely used in computer vision and graphics for 3D model acquisition. This paper describes a new and simple method for recovering the geometry of uncalibrated circular motion from a minimal set of only two points in four images. This problem has been previously solved using nonminimal data either by computing the fundamental matrix and trifocal tensor in three images or by fitting conics to tracked points in five or more images. It is first established that two sets of tracked points in different images under circular motion for two distinct space points are related by a homography. Then, we compute a plane homography from a minimal two points in four images. After that, we show that the unique pair of complex conjugate eigenvectors of this homography are the image of the circular points of the parallel planes of the circular motion. Subsequently, all other motion and structure parameters are computed from this homography in a straighforward manner. The experiments on real image sequences demonstrate the simplicity, accuracy, and robustness of the new method.