Harmonic Embeddings for Linear Shape Analysis

We present a novel representation of shape for closed contours in ℝ² or for compact surfaces in ℝ³ explicitly designed to possess a linear structure. This greatly simplifies linear operations such as averaging, principal component analysis or differentiation in the space of shapes when compared to more common embedding choices such as the signed distance representation linked to the nonlinear Eikonal equation. The specific choice of implicit linear representation explored in this article is the class of harmonic functions over an annulus containing the contour. The idea is to represent the contour as closely as possible by the zero level set of a harmonic function, thereby linking our representation to the linear Laplace equation. We note that this is a local represenation within the space of closed curves as such harmonic functions can generally be defined only over a neighborhood of the embedded curve. We also make no claim that this is the only choice or even the optimal choice within the class of possible linear implicit representations. Instead, our intent is to show how linear analysis of shape is greatly simplified (and sensible) when such a linear representation is employed in hopes to inspire new ideas and additional research into this type of linear implicit representations for curves. We conclude by showing an application for which our particular choice of harmonic representation is ideally suited.     

Convolution Filtering of Continuous Signed Distance Fields for Polygonal Meshes

Signed distance fields obtained from polygonal meshes are commonly used in various applications. However, they can have C¹ discontinuities causing creases to appear when applying operations such as blending or metamorphosis. The focus of this work is to efficiently evaluate the signed distance function and to apply a smoothing filter to it while preserving the shape of the initial mesh. The resulting function is smooth almost everywhere, while preserving the exact shape of the polygonal mesh. Due to its low complexity, the proposed filtering technique remains fast compared to its main alternatives providing C¹‐continuous distance field approximation. Several applications are presented such as blending, metamorphosis and heterogeneous modelling with polygonal meshes.     

3-D curve matching using splines

A machine vision algorithm to find the longest common subcurve of two 3-D curves is presented. The curves are represented by splines fitted through sequences of sample points extracted from dense range data. The approximated 3-D curves are transformed into 1-D numerical strings of rotation and translation invariant shape signatures, based on a multiresolution representation of the curvature and torsion values of the space curves. The shape signature strings are matched using an efficient hashing technique that finds longest matching substrings. The results of the string matching stage are later verified by a robust, least-squares, 3-D curve matching technique, which also recovers the Euclidean transformation between the curves being matched. This algorithm is of average complexity O(n) where n is the number of the sample points on the two curves. The algorithm has applications in assembly and object recognition tasks. Results of assembly experiments are included.     

A class of general quartic spline curves with shape parameters

With a support on four consecutive subintervals, a class of general quartic splines are presented for a non-uniform knot vector. The splines have C² continuity at simple knots and include the cubic non-uniform B-spline as a special case. Based on the given splines, piecewise quartic spline curves with three local shape parameters are given. The given spline curves can be C²∩G³ continuous by fixing some values of the curve?s parameters. Without solving a linear system, the spline curves can also be used to interpolate sets of points with C² continuity. The effects of varying the three shape parameters on the shape of the quartic spline curves are determined and illustrated.     

Curvature continuous offset approximation based on circle approximation using quadratic Bézier biarcs

We present a method for G² end-point interpolation of offset curves using rational Bézier curves. The method is based on a G² end-point interpolation of circular arcs using quadratic Bézier biarcs. We also prove the invariance of the Hausdorff distance between two compatible curves under convolution. Using this result, we obtain the exact Hausdorff distance between an offset curve and its approximation by our method. We present the approximation algorithm and give numerical examples.     

Evolving Guide Subdivision

To overcome the well-known shape deficiencies of bi-cubic subdivision surfaces, Evolving Guide subdivision (EG subdivision) generalizes C² bi-quartic (bi-4) splines that approximate a sequence of piecewise polynomial surface pieces near extraordinary points. Unlike guided subdivision, which achieves good shape by following a guide surface in a two-stage, geometry-dependent process, EG subdivision is defined by five new explicit subdivision rules. While formally only C¹ at extraordinary points, EG subdivision applied to an obstacle course of inputs generates surfaces without the oscillations and pinched highlight lines typical for Catmull-Clark subdivision. EG subdivision surfaces join C² with bi-3 surface pieces obtained by interpreting regular sub-nets as bi-cubic tensor-product splines and C² with adjacent EG surfaces. The EG subdivision control net surrounding an extraordinary node can have the same structure as Catmull-Clark subdivision: two rings of 4-sided facets around each extraordinary nodes so that extraordinary nodes are separated by at least one regular node.     

Spatiotemporal salient points for visual recognition of human actions.

This paper addresses the problem of human-action recognition by introducing a sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time. The spatiotemporal salient points are detected by measuring the variations in the information content of pixel neighborhoods not only in space but also in time. An appropriate distance metric between two collections of spatiotemporal salient points is introduced, which is based on the chamfer distance and an iterative linear time-warping technique that deals with time expansion or time-compression issues. A classification scheme that is based on relevance vector machines and on the proposed distance measure is proposed. Results on real image sequences from a small database depicting people performing 19 aerobic exercises are presented.     

Some smoothness conditions and conformality conditions for bivariate quartic and quintic splines

This paper is concerned with a study of some new formulations of smoothness conditions and conformality conditions for multivariate splines in terms of B-net representation. In the bivariate setting, a group of new parameters of bivariate quartic and quintic polynomials over a planar simplex is introduced, new formulations of smoothness conditions of bivariate quartic C ¹ splines and quintic C ² splines are given, and the conformality conditions of bivariate quartic C ¹ splines are simplified. Received: February 1998 / Accepted: August 1998     

Shape-preserving interpolation of irregular data by bivariate curvature-based cubic splines in spherical coordinates

We investigate C¹-smooth bivariate curvature-based cubic L₁ interpolating splines in spherical coordinates. The coefficients of these splines are calculated by minimizing an integral involving the L₁ norm of univariate curvature in four directions at each point on the unit sphere. We compare these curvature-based cubic L₁ splines with analogous cubic L₂ interpolating splines calculated by minimizing an integral involving the square of the L₂ norm of univariate curvature in the same four directions at each point. For two sets of irregular data on an equilateral tetrahedron with protuberances on the faces, we compare these two types of curvature-based splines with each other and with cubic L₁ and L₂ splines calculated by minimizing the L₁ norm and the square of the L₂ norm, respectively, of second derivatives. Curvature-based cubic L₁ splines preserve the shape of irregular data well, better than curvature-based cubic L₂ splines and than second-derivative-based cubic L₁ and L₂ splines. Second-derivative-based cubic L₂ splines preserve shape poorly. Variants of curvature-based L₁ and L₂ splines in spherical and general curvilinear coordinate systems are outlined.