Using image morphing for memory-efficient impostor rendering on GPU

Real-time rendering of large animated crowds consisting thousands of virtual humans is important for several applications including simulations, games and interactive walkthroughs; but cannot be performed using complex polygonal models at interactive frame rates. For that reason, several methods using large numbers of pre-computed image-based representations, which are called as impostors, have been proposed. These methods take the advantage of existing programmable graphics hardware to compensate the computational expense while maintaining the visual fidelity. Making the number of different virtual humans, which can be rendered in real-time, not restricted anymore by the required computational power but by the texture memory consumed for the variety and discretization of their animations. In this work, we proposed an alternative method that reduces the memory consumption by generating compelling intermediate textures using image-morphing techniques. In order to demonstrate the preserved perceptual quality of animations, where half of the key-frames were rendered using the proposed methodology, we have implemented the system using the graphical processing unit and obtained promising results at interactive frame rates

Morphological shape generation through user-controlled group metamorphosis

Morphological shape design is interpreted in this paper as a search for new shapes from a particular application domain represented by a set of selected shape instances. This paper proposes a new foundation for morphological shape design and generation. In contrast to existing generative procedures, an approach based on a user-controlled metamorphosis between functionally based shape models is presented. A formulation of the pairwise metamorphosis is proposed with a variety of functions described for the stages of deformation, morphing and offsetting. This formulation is then extended to the metamorphosis between groups of shapes with user-defined, dynamically correlated and weighted feature elements. A practical system was implemented in the form of plugin to Maya and tested by an industrial designer on a group of representative shapes from a particular domain. © 2013 Elsevier Ltd

The Collective Building of Knowledge in Collaborative Learning Environments

The intention of this chapter is to investigate how collaborative learning environments (CLEs) can be used to elicit the collective building of knowledge. This work discusses CLEs as lively cognitive systems and looks at some strategies that might contribute to the improvement of significant pedagogical practices. The study is supported by rhizome principles, whose characteristics allow us to understand the process of selecting and connecting what is relevant and meaningful for the collective building of knowledge. A brief theoretical and conceptual approach is presented and major contributions and difficulties about collaborative learning environments are discussed. New questions and future trends about the collective building of knowledge are suggested

Gettysburg: Our College\u27s Magazine Winter 2018

From the President Janet Morgan Riggs \u2777 Table of Contents Virtual Dissection Tables to Enhance Study of Anatomy Prof Notes: Jennifer Bloomquist (Professor Jennifer Bloomquist) Life\u27s Lessons Learned from Sports & Science (Sarah Hansen \u2717, Alex Posch \u2714) The 411: Allison Meckley \u2705 For the Love of Data (Svet Semov \u2711, Shannon Brobst \u2715) Snapshots They Inquire, They Inspire Gettysburgreat: The Campaign for Our College Media Notes (Professor John B. Zinn) Conversations The Best of Both Worlds Andrew Milone \u2718 Metamorphosis: Professor Kay Etheridge Carina Sitkus Our Endowment and Why It Matters Mike Baker Hope is in the Genes: Louis M. Kunkel \u2771 Carina Sitkus What Students Do: Interns at Cannes (Robert Sharpe \u2717, Nick Merrit \u2718) Work that Makes a Difference: Art Pros from the Gettysburg Network (Laura Elizabeth Barone Shea \u2710, Emily Francisco \u2714, Elizabeth Petersen \u2710, Sarah Parker \u2713, Rebecca Duffy \u2716, Molly Reynolds \u2714) What Makes Gettysburg Great: Actual and Virtual Treasure Save the Dates Class Notes In Memory We Remember President Emeritus Gordon A. Haaland Share Your Dreams & Inspiration (Marion McKenzie ’19)https://cupola.gettysburg.edu/gburgmag/1012/thumbnail.jp

Topic maps aplicados ao sistema de informação do Museu da Emigração

O presente artigo apresenta uma aplicação do Metamorphosis ao caso do Museu Virtual da Emigração. O Museu da Emigração contém no seu espólio fontes de informação compostas por documentos XML e por uma base de dados relacional. A função do Metamorphosis é propiciar uma visão homogénea destes recursos através da criação de um topic map que represente este universo de discurso. Para isso, usa-se o Oveia para a extracção do topic map e o Ulisses para a navegação sobre o conhecimento do domínio. O resultado é uma visão integrada do Museu da Emigração, de acordo com a ontologia especificada pelo projectista

Differential expression of three galaxin-related genes during settlement and metamorphosis in the scleractinian coral Acropora millepora

BACKGROUND: The coral skeleton consists of CaCO3 deposited upon an organic matrix primarily as aragonite. Currently galaxin, from Galaxea fascicularis, is the only soluble protein component of the organic matrix that has been characterized from a coral. Three genes related to galaxin were identified in the coral Acropora millepora. RESULTS: One of the Acropora genes (Amgalaxin) encodes a clear galaxin ortholog, while the others (Amgalaxin-like 1 and Amgalaxin-like 2) encode larger and more divergent proteins. All three proteins are predicted to be extracellular and share common structural features, most notably the presence of repetitive motifs containing dicysteine residues. In situ hybridization reveals distinct, but partially overlapping, spatial expression of the genes in patterns consistent with distinct roles in calcification. Both of the Amgalaxin-like genes are expressed exclusively in the early stages of calcification, while Amgalaxin continues to be expressed in the adult, consistent with the situation in the coral Galaxea. CONCLUSION: Comparisons with molluscs suggest functional convergence in the two groups; lustrin A/pearlin proteins may be the mollusc counterparts of galaxin, whereas the galaxin-like proteins combine characteristics of two distinct proteins involved in mollusc calcification. Database searches indicate that, although sequences with high similarity to the galaxins are restricted to the Scleractinia, more divergent members of this protein family are present in other cnidarians and some other metazoans. We suggest that ancestral galaxins may have been secondarily recruited to roles in calcification in the Triassic, when the Scleractinia first appeared. Understanding the evolution of the broader galaxin family will require wider sampling and expression analysis in a range of cnidarians and other animals