Multiple View Geometry of General Algebraic Curves

We introduce a number of new results in the context of multi-view geometry from general algebraic curves. We start with the recovery of camera geometry from matching curves. We first show how one can compute, without any knowledge on the camera, the homography induced by a single planar curve. Then we continue with the derivation of the extended Kruppa's equations which are responsible for describing the epipolar constraint of two projections of a general algebraic curve. As part of the derivation of those constraints we address the issue of dimension analysis and as a result establish the minimal number of algebraic curves required for a solution of the epipolar geometry as a function of their degree and genus.We then establish new results on the reconstruction of general algebraic curves from multiple views. We address three different representations of curves: (i) the regular point representation in which we show that the reconstruction from two views of a curve of degree d admits two solutions, one of degree d and the other of degree d(d – 1). Moreover using this representation, we address the problem of homography recovery for planar curves, (ii) dual space representation (tangents) for which we derive a lower bound for the number of views necessary for reconstruction as a function of the curve degree and genus, and (iii) a new representation (to computer vision) based on the set of lines meeting the curve which does not require any curve fitting in image space, for which we also derive lower bounds for the number of views necessary for reconstruction as a function of curve degree alone.     

Dynamic active contours for visual tracking

Visual tracking using active contours is usually set in a static framework. The active contour tracks the object of interest in a given frame of an image sequence. A subsequent prediction step ensures good initial placement for the next frame. This approach is unnatural; the curve evolution gets decoupled from the actual dynamics of the objects to be tracked. True dynamical approaches exist, all being marker particle based and thus prone to the shortcomings of such particle-based implementations. In particular, topological changes are not handled naturally in this framework. The now classical level set approach is tailored for evolutions of manifolds of codimension one. However, dynamic curve evolution is at least a codimension two problem. We propose an efficient, level set based approach for dynamic curve evolution, which addresses the artificial separation of segmentation and prediction while retaining all the desirable properties of the level set formulation. It is based on a new energy minimization functional which, for the first time, puts dynamics into the geodesic active contour framework.     

基于测地回归模型的颅面复原

颅面复原是指根据一个未知颅骨的特征预测出对应的面貌,在考古研究、医学整容、刑事案件调查等领域有重要应用.为解决颅面复原过程中存在着数据量大、需要大量标定特征点的手工工作及颅面特征点定义困难的问题,针对三角网格表示的三维颅骨和面皮模型,将颅面模型用从鼻尖出发的一组测地线表示,提出了基于测地回归的颅面复原方法.该方法首先从三维人脸模型的鼻尖点提取一组测地线;然后以颅骨和对应的人脸模型上提取的测地线作为训练样本,采用偏最小二乘回归统计模型复原未知颅骨对应人脸模型的测地线;最后通过迭代最近点算法将生成的测地线与人脸统计模型进行匹配,实现复原测试颅骨的面貌.在192套颅面数据库上进行了颅面复原实验,将基于测地回归法复原的结果与主成分分析法和偏最小二乘回归法复原结果对比,实验结果表明,该方法能够提高复原精度,减少复原时间,取得了良好的复原效果.     

Deformation similarity measurement in quasi-conformal shape space

This paper presents a novel approach based on the shape space concept to classify deformations of 3D models. A new quasi-conformal metric is introduced which measures the curvature changes at each vertex of each pose during the deformation. The shapes with similar deformation patterns follow a similar deformation curve in shape space. Energy functional of the deformation curve is minimized to calculate the geodesic curve connecting two shapes on the shape space manifold. The geodesic distance illustrates the similarity between two shapes, which is used to compute the similarity between the deformations. We applied our method to classify the left ventricle deformations of myopathic and control subjects, and the sensitivity and specificity of our method were 88.8% and 85.7%, which are higher than other methods based on the left ventricle cavity, which shows our method can quantify the similarity and disparity of the left ventricle motion well.     

Geodesic-Controlled Developable Surfaces for Modeling Paper Bending

We present a novel and effective method for modeling a developable surface to simulate paper bending in interactive and animation applications. The method exploits the representation of a developable surface as the envelope of rectifying planes of a curve in 3D, which is therefore necessarily a geodesic on the surface. We manipulate the geodesic to provide intuitive shape control for modeling paper bending. Our method ensures a natural continuous isometric deformation from a piece of bent paper to its flat state without any stretching. Test examples show that the new scheme is fast, accurate, and easy to use, thus providing an effective approach to interactive paper bending. We also show how to handle non-convex piecewise smooth developable surfaces.     

Efficiently computing geodesic offsets on triangle meshes by the extended Xin–Wang algorithm

Geodesic offset curves are important for many industrial applications, such as solid modeling, robot-path planning, the generation of tool paths for NC machining, etc. Although the offset problem is well studied in classical differential geometry and computer-aided design, where the underlying surface is sufficiently smooth, very few algorithms are available for computing geodesic offsets on discrete representation, in which the input is typically a polyline curve restricted on a piecewise linear mesh. In this paper, we propose an efficient and exact algorithm to compute the geodesic offsets on triangle meshes by extending the Xin–Wang algorithm of discrete geodesics. We define a new data structure called parallel-source windows, and extend both the “one angle one split” and the filtering theorem to maintain the window tree. Similar to the original Xin–Wang algorithm, our extended algorithm has an O(n) space complexity and an O(n²logn) asymptotic time complexity, where n is the number of vertices on the input mesh. We tested our algorithm on numerous real-world models and showed that our algorithm is exact, efficient and robust, and can be applied to large scale models with complicated geometry and topology.     

Parametric representation of a surface pencil with a common spatial geodesic

In this paper, we study the problem of constructing a family of surfaces from a given spatial geodesic curve. We derive a parametric representation for a surface pencil whose members share the same geodesic curve as an isoparametric curve. By utilizing the Frenet trihedron frame along the given geodesic, we express the surface pencil as a linear combination of the components of this local coordinate frame, and derive the necessary and sufficient conditions for the coefficients to satisfy both the geodesic and the isoparametric requirements. We illustrate and verify the method by finding exact surface pencil formulations for some simple surfaces, such as surfaces of revolution and ruled surfaces. Finally, we demonstrate the use of this method in a garment design application.     

Geodesic Polar Coordinates on Polygonal Meshes

Geodesic Polar Coordinates (GPCs) on a smooth surface S are local surface coordinates that relates a surface point to a planar parameter point by the length and direction of a corresponding geodesic curve onS . They are intrinsic to the surface and represent a natural local parameterization with useful properties. We present a simple and efficient algorithm to approximate GPCs on both triangle and general polygonal meshes. Our approach, named DGPC, is based on extending an existing algorithm for computing geodesic distance. We compare our approach with previous methods, both with respect to efficiency, accuracy and visual qualities when used for local mesh texturing. As a further application we show how the resulting coordinates can be used for vector space methods like local remeshing at interactive frame‐rates even for large meshes.     

G 2 interpolation and blending on surfaces

We introduce a method for curvature-continuous (G ²) interpolation of an arbitrary sequence of points on a surface (implicit or parametric) with prescribed tangent and geodesic curvature at every point. The method can also be used forG ² blending of curves on surfaces. The interpolation/blending curve is the intersection curve of the given surface with a functional spline (implicit) surface. For the construction of blending curves, we derive the necessary formulas for the curvature of the surfaces. The intermediate results areG ² interpolation/blending methods in IR².     

Regularized Laplacian Zero Crossings as Optimal Edge Integrators

We view the fundamental edge integration problem for object segmentation in a geometric variational framework. First we show that the classical zero-crossings of the image Laplacian edge detector as suggested by Marr and Hildreth, inherently provides optimal edge-integration with regard to a very natural geometric functional. This functional accumulates the inner product between the normal to the edge and the gray level image-gradient along the edge. We use this observation to derive new and highly accurate active contours based on this functional and regularized by previously proposed geodesic active contour geometric variational models. We also incorporate a 2D geometric variational explanation to the Haralick edge detector into the geometric active contour framework.