We propose a new algorithm for stereoscopic depth perception, where the depth map is the momentary state of a dynamic process. To each image point we assign a set of possible disparity values. In a dynamic process with competition and cooperation, the correct disparity value is selected for each image point. Therefore, we solve the correspondence problem by a dynamic, self-organizing process, the structure of which shows analogies to the human visual system. The algorithm can be implemented in a massive parallel manner and yields good results for either artificial or natural images.
Objetivos: Este estudo teve como um de seus objetivos avaliar a presença de enteroparasitos em crianças que frequentavam um Centro de Educação Municipal Infantil (CMEI) de Rondonópolis - MT. Métodos: Foram realizadas as coletas das amostras fecais no período de março a maio de 2016 e, posteriormente, analisadas pelo método de Hoffman, Pons e Janer (HPJ) no laboratório de Ciências Básicas da Universidade Federal de Mato Grosso, Campus Universitário de Rondonópolis, finalizando com um questionário sócio demográfico de fatores de risco para a infecção. Resultados: Entre as 57 crianças pesquisadas, detectou-se positividade para enteroparasitoses em 10 (17,54%) delas, o parasita mais prevalente foi a Giardia lamblia (70%). Em relação ao sexo, a maior positividade das amostras se deu entre crianças do sexo masculino. Conclusão: Os achados dessa pesquisa demonstram que, embora o Ministério da Saúde venha aplicando medidas de controle dos enteroparasitos como o Programa Saúde na Escola, mais medidas deverão ser tomadas, principalmente pelos profissionais de saúde da Atenção Primária. Uma medida simples e eficaz é a educação em saúde executada de forma específica para a conscientização dessas crianças e de seus responsáveis sobre cuidados e higienização para uma melhor qualidade de vida.
We introduce a dynamical model for automatic vergence eye movement control. In connection with our dynamical system of binocular model neurons that solves the correspondence problem of stereo-vision, we present a complete model for stereo-vision. Our automatic vergence eye movement control adjusts an image segment, which is of momentary interest to the observer. The adjustment is done in such a way that we only need to define a disparity search range of minimal extension. Recently, a new method of encoding (3D) three-dimensional information in 2D pictures was designed in the form of computer-generated patterns of colored dots. At first glimpse, these so-called autostereograms appear as structured but meaningless patterns. After a certain period of observation, a 3D pattern emerges suddenly in an impressive way. Applying our algorithm to autostereograms, we find a fully satisfactory agreement with the multivalent perception experienced by humans. As in nature, in our model the phase transition between the initial state and the 3D perception state takes place in a very short time. Our algorithm is very robust against noise, and there is no need to interpolate a sparse depth map.
Der synergetische Computer, zunächst als Anwendung synergetischer Prinzipien mehr von akademischem Interesse, findet neuerdings Eingang in industrielle Anwendungen. Zugleich wurde sein Konzept erweitert, und Hardware‐Realisierungen durch Halbleiter zeichnen sich ab.
We propose a new algorithm for stereoscopic depth perception, where the depth map is the momentary state of a dynamic process. To each image point we assign a set of possible disparity values. In a dynamic process with competition and cooperation, the correct disparity value is selected for each image point. Therefore, we solve the correspondence problem by a dynamic, self-organizing process, the structure of which shows analogies to the human visual system. The algorithm can be implemented in a massive parallel manner and yields good results for either artificial or natural images.
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