Claudio Castellanos Sánchez

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Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired(More)
In this paper we present a bio-inspired connectionist model for visual perception of motion and its pursuit. It is organized in three stages: a causal spatio-temporal filtering of Gabor-like type, an antagonist inhibition mechanism and a densely interconnected neural population. These stages are inspired by the treatment of the primary visual cortex, middle(More)
In this paper we propose a bio-inspired architecture to detect , describe and distinguish objects in motion. By using neuronal and physiological mechanisms in primary visual cortex (V1), middle temporal (MT) and inferotemporal (IT) areas we can start isolating the objects from their environment; then, track, label and distinguish the humans from non-human(More)
—The modeling of quasi-static optimization problems often involves divergence-free surface current densities. In this paper, a novel technique to implement these currents by using the boundary element method framework is presented. A locally-based characterization of the current density is employed, to render a fully geometry-independent formulation, so(More)