collections of shapes are becoming freely available, and we will soon need tools that quickly give an overview of the contents of a shape database. We present a browsing tool that produces a hierarchical, cluster-based overview of a shape collection, and allows users to zoom in on individual clusters to get

Figure 1: Given a shape collection, our system creates a mutually abstracted set. We compute a spectrum of abstractions for each model. The most appropriate abstraction level is then determined in relation to other abstractions in the collection. When a collection includes geometrically similar

Extracting semantically related parts across models remains challenging, especially without supervision. The common approach is to co-analyze a model collection, while assuming the existence of descriptive geometric features that can directly identify related parts. In the presence of large shape

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version

of its three-dimensional position, orientation, and the lighting conditions. Such a problem is challenging because faces are nonrigid and have a high degree of variability in size, shape, color, and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose

’ it back to 3D, by exploiting a collection of aligned 3D models of related objects shape. Our key insight is that, even when the imaged object is not contained in the shape collection, the network of shapes implicitly characterizes a shape-specific de-formation subspace that regularizes the problem

This book is about culture and memory, about how the society and culture in which people grow up helps to determine their individual memories, collective memories, and identity. We will emphasize how the process of repeated retrieval helps to shape our memories. Before we get to our main story, we

In this paper are presented the results of numerical calculation of electrical characteristics in an electrostatic precipitator with so called sigma collecting electrodes. Calculations are performed by using finite volume numerical method. The significant features of this method are simple

fragmentation, whereas the second and third algorithms both lead to flocking. A systematic method is provided for construction of cost functions (or collective potentials) for flocking. These collective potentials penalize deviation from a class of lattice-shape objects called αlattices. We use a multi

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