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VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world.This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR.At the advent of V ...
Algorithms for distributed agreement are a powerful means for formulating distributed versions of existing centralized algorithms. We present a toolkit for this task and show how it can be used systematically to design fully distributed algorithms for stat ...
Creating digital representations of humans is of utmost importance for applications ranging from entertainment (video games, movies) to human-computer interaction and even psychiatrical treatments. What makes building credible digital doubles difficult is ...
In this paper we present a new methodology to extract the small error-prone motion recorded during a Computed Tomography (CT) imaging directly from the sinogram. In comparison to the use of the usual reconstructed images, this approach has the advantage to ...
The SCRBE (Static-Condensation Reduced-Basis-Element) method is a component-to-system model order reduction approach for efficient many-query and real-time treatment of linear partial differential equations characterized by many spatially distributed const ...
We have analyzed structural motifs in the Deem database of hypothetical zeolites to investigate whether the structural diversity found in this database can be well-represented by classical descriptors, such as distances, angles, and ring sizes, or whether ...
In many signal processing, machine learning and computer vision applications, one often has to deal with high dimensional and big datasets such as images, videos, web content, etc. The data can come in various forms, such as univariate or multivariate time ...
Capturing and processing human geometry, appearance, and motion is at the core of computer graphics, computer vision, and human-computer interaction. The high complexity of human geometry and motion dynamics, and the high sensitivity of the human visual sy ...
Conventional linear subspace learning methods like principal component analysis (PCA), linear discriminant analysis (LDA) derive subspaces from the whole data set. These approaches have limitations in the sense that they are linear while the data distribut ...
Institute of Electrical and Electronics Engineers2011
Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...
