The increasing availability of object-based video content requires new technologies for automatically extracting and matching of the low level features of arbitrarily shaped video. In this paper, methods for shape retrieval of arbitrarily shaped video objects are proposed. Along with still shape features the shape deformations that may occur in an object’s life span is also taken. In this paper...

This paper presents a novel 2D shape deformation algorithm based on nonlinear least squares optimization. The algorithm aims to preserve two local shape properties: Laplacian coordinates of the boundary curve and local area of the shape interior, which are together represented in a non-quadric energy function. An iterative Gauss-Newton method is used to minimize this nonlinear energy function. ...

Analysis of shape variability is important for diagnostic classification and understanding of biological processes. We present a novel shape analysis approach based on a multiscale medial representation. Our method examines shape variability in separate categories, such as global variability in the coarse-scale shape description and localized variability in the fine-scale description. The metho...

A novel geometric framework for decomposition of tensor distance into shape and orientation distances is proposed. We show that such shape distance leads to the development of a novel and robust anisotropy measure that reveals strikingly superior white matter profile of DT-MR brain images than fractional anisotropy (FA) and analytically show that it has a higher signal to noise ratio than FA. U...

We propose a novel technique, termed compact shape trees, for computing correspondences of single-boundary 2-D shapes in O(n) time. Together with zero or more features defined at each of n sample points on the shape’s boundary, the compact shape tree of a shape comprises the O(n) collection of vectors emanating from any of the sample points on the shape’s boundary to the rest of the sample poin...

We introduce techniques for the processing of motion and animations of non-rigid shapes. The idea is to regard animations of deformable objects as curves in shape space. Then, we use the geometric structure on shape space to transfer concepts from curve processing in Rn to the processing of motion of non-rigid shapes. Following this principle, we introduce a discrete geometric flow for curves i...

This paper describes a class of lightweight structures known as compliant shell mechanisms. These are novel reconfigurable solutions for advanced structures, such as morphing shells and deployable membranes. They have local, discrete corrugations, which articulate and deform to achieve dramatic changes in the overall shape of the shell. The unique kinematics are considered by highlighting examp...

In this work we present an automatic shape extraction and classification method for face and eye-ware shapes. Our novel eye-ware shape extraction algorithm can extract the polygonal shape of eyeware accurately and reliably even for reflective sun-glasses and thin metal frames. Additionally, we identify key geometric features that can differentiate reliably the shape classes and we integrate the...

An af®ne-invariant (AI) deformable contour model for object matching, called AI-EigenSnake (AI-ES), is proposed in the Bayesian framework. In AI-ES, the prior distribution of object shapes is estimated from the sample data. This distribution is then used to constrain the prototype contour, which is dynamically adjustable in the matching process. In this way, large shape deformations due to the ...