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To automatically register foreground target in cluttered images, we present a novel hierarchical graph representation and a stochastic computing strategy in Bayesian framework. The graph representation, which contains point-(image primitives), seedgraph-, and subgraph- three levels, are built up following the primal sketch theory to capture geometric, topological, and spatial information both in local...
As a supervised learning algorithm, the standard Gaussian processes has the excellent performance of classification. In this paper, we present a semi-supervised algorithm to learning a Gaussian process classifier, which incorporating a graph-based construction of semi-supervised kernels in the presence of labeled and unlabeled data, and expanding the standard Gaussian processes algorithm into the...
Most of 3D modeling tools' operating interface are complex. In this paper, a fast free sketching 3D modeling method with edge understanding approached. Free sketching is this method's input. A 3D model was constructed in a short time. Some self-intersection graph can be recognized though add some edge index information in this method.
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