Modelagem paralela em C+CUDA de sistema neural de visão esteroscópica

• Ano de defesa: 2009
• Autor(a) principal: Carvalho, Camilo Alves
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Informática; Centro Tecnológico; UFES; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: C+CUDA (Linguagem de programação de computador); Computação de alto desempenho; Visão artificial; Ciência da Computação; 004
• Link de acesso: http://repositorio.ufes.br/handle/10/4208

The images formed on our retinae are bidimensional; however, from them our brain is capable of synthesizing a 3D representation with color, shape and depth information about the objects in the surrounding environment. For that, after choosing a point in 3D space, our eyes verge to this point and, at the same time, the visual system is fed back with the eyes position information, interpreting it as the distance of this point to the observer. Depth perception around the vergence point is obtained using visual disparity, i.e., the difference between the positions in the retinae of the two projections of a given point in 3D space caused by the horizontal separation of the eyes. Most of the depth perception processing is done in the visual cortex, mainly in the primary (V1) and medial temporal (MT) areas. In this work, we developed a parallel implementation in C+CUDA of model, built at UFES, of the neural architecture of the V1 and MT cortices that uses as building blocks previous models of cortical cells and log-polar mapping. A sequential implementation of this model can create tridimensional representations of the external world using stereoscopic image pairs obtained from a pair of fronto-parallel cameras. Our C+CUDA parallel implementation is almost 60 times faster and allows real-time 3D reconstruction.