We present a geometric approach to statistical shape analysis of closed curves in images. The basic idea is to specify a space of closed curves satisfying given constraints, and exploit the differential geometry of this space to solve optimization and inference problems. We demonstrate this approach by: (i) defining and computing statistics of observed shapes, (ii) defining and learning a param...

Shape is one of the most important properties of objects. This lecture summarizes the algorithms for shape analysis. Several commonly used simple descriptors are stated first. Then the algorithms are classified into boundary (or external) descriptors and regional (or internal) descriptors based on the boundary tracking only and boundary plus the interior tracking respectively. The characteristi...

We present a new framework for multidimensional shape analysis. The proposed framework represents solid objects as points on an infinite-dimensional Riemannian manifold and distances between objects as minimal length geodesic paths. Intershape distance forms the foundation for shape-based statistical analysis. The proposed method incorporates a metric that naturally prevents self-intersections ...

In this paper, I will describe a computer vision-based musical performance system that uses morphological assessments to provide control data. Using shape analysis allows the system to provide qualitative descriptors of the scene being captured while ensuring its use in a wide variety of different settings. This system was implemented under Max/MSP/Jitter, augmented with a number of external ob...

In this paper, we present a methodology for performing statistical analysis for image-based studies of differences between populations and describe our experience applying the technique in several different population comparison experiments. Unlike traditional analysis tools, we consider all features simultaneously, thus accounting for potential correlations between the features. The result of ...

In recent years, substantial progress in shape analysis has been achieved through methods that use the spectra and eigenfunctions of discrete Laplace operators. In this work, we study spectra and eigenfunctions of discrete differential operators that can serve as an alternative to the discrete Laplacians for applications in shape analysis. We construct such operators as the Hessians of surface ...

Skeletonization will probably become as valuable a tool for shape analysis in 3D, as it is in 2D. We present a topology preserving 3D skeletonization method which computes both surface and curve skeletons whose voxels are labelled with the D6 distance to the original background. The surface skeleton preserves all shape information, so (close to) complete recovery of the object is possible. The ...

W 4 is a real time visual surveillance system for detecting and tracking people and monitoring their activities in an outdoor environment. It operates on monocular grayscale video imagery, or on video imagery from an infrared camera. Unlike many of systems for tracking people, W 4 makes no use of color cues. Instead, W 4 employs a combination of shape analysis and tracking to locate people and ...

Decomposition of shapes into (approximate) convex parts is essential for applications such as part-based shape representation, shape matching, and collision detection. In this paper, we propose a novel convex decomposition using a parametric implicit shape model called Disjunctive Normal Shape Model (DNSM). The DNSM is formed as a union of polytopes which themselves are formed by intersections ...

This study focuses on a feature extraction algorithm for classification of marble tiles. The color content and vein distribution are considered to be the main criteria for classification. A color segmentation algorithm is used for detection of veins. The shape analysis of the veins are done by utilizing the distance image.