Abstract

Abstract
One of the most challenging tasks for an animator is to quickly create convincing facial expressions. Finding an effective control interface to manipulate facial geometry has traditionally required experienced users (usually technical directors), who create and place the necessary animation controls. Here we present our sketching interface control system, designed to reduce the time and effort necessary to create facial animations. Inspired in the way artists draw, where simple strokes define the shape of an object, our approach allows the user to sketch such strokes either directly on the 3D mesh or on two different types of canvas: a 2D fixed canvas or more flexible 2.5D dynamic screen-aligned billboards. In all cases, the strokes do not control the geometry of the face, but the underlying animation rig instead, allowing direct manipulation of the rig elements. Additionally, we show how the strokes can be easily reused in different characters, allowing retargeting of poses on several models. We illustrate our interactive approach using varied facial models of different styles showing that first time users typically create appealing 3D poses and animations in just a few minutes. We also present in this article the results of a user study. We deploy our method in an application for an artistic purpose. Our system has also been used in a pioneer serious game context, where the goal was to teach people with Autism Spectrum Disorders (ASD) to recognize facial emotions, using real time synthesis and automatic facial expression analysis.

Abstract

Abstract
SIARD Suite enables us to preserve a relational database in an open format. It migrates a relational database to SIARD format and preserves technical and contextual metadata along with the primary data ensuring long term accessibility. This paper introduces a web application, the SIARD Archive Browser, which allows operations on the archive such as searching for a specific record, counting records in a table containing a keyword, sorting by a column and making joins. In many use cases, the application avoids the need to load a preserved database to a DBMS. © 2012 Springer-Verlag.

Abstract

Abstract
Selecting the right set of descriptors for the annotation of a specific dataset can be a hard problem in research data management. Considering a dataset in an arbitrary domain, an application profile is complex to build because of the abundance of metadata standards, ontologies and other descriptor sources available for different domains. We propose to partially automate the process of data description by generating application profile recommendations based on a research data asset knowledge base. Our approach builds on existing technologies for exploring linked data and results in a process which can be tightly coupled with the research workflow, giving researchers more control over the description of their data. Preliminary experiments show that we can build on state-of-the-art technologies for search indexes, graph databases and triple stores to explore existing sources of linked data for our profile generation.