Henry Braun

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Simulation of everyday situations from real life can be a very useful tool in entertainment applications and training systems. Such applications, as games or computer animated movies usually need to provide virtual environments populated with virtual autonomous agents. Commonly, the agents need to be able to evolve in their environment, avoiding collision(More)
In this paper we present a platform called VhCVE, in which relevant issues related to Collaborative Virtual Environments applications are integrated. The main goal is to provide a framework where participants can interact with others by voice and chat. Also, manipulation tools such as a mouse using Computer Vision and Physics are included, as well as(More)
Photovoltaics (PV) is an important and rapidly growing area of research. With the advent of power system monitoring and communication technology collectively known as the " smart grid, " an opportunity exists to apply signal processing techniques to monitoring and control of PV arrays. In this paper a monitoring system which provides real-time measurements(More)
Crowd visualization is present mostly in digital games and computer animated movies, but are also observed in simulations and virtual reality applications. In crowd simulations we should represent the behavior of agents given different scenarios, and also, such simulations can be provided by different softwares and tools. This paper presents a framework for(More)
Figure 1: In (a) and (c) real images of cracks in concrete are presented. In (b) and (d), results obtained with our model based on Leaf venation method are illustrated. Abstract This paper presents a model for generating 2D cracks in real-time for application in games and cartoon animations. Cracks are generated based on a method previously used for leaf(More)
—The compressive sensing paradigm holds promise for more cost-effective imaging outside of the visible range, particularly in infrared wavelengths. However, the process of reconstructing compressively sensed images remains computa-tionally expensive. The proof-of-concept tracker described here uses a particle filter with a likelihood update based on a "(More)
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