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1.
Stephen J. Maybank 《International Journal of Computer Vision》2007,72(3):287-307
The parameter space for the ellipses in a two dimensional image is a five dimensional manifold, where each point of the manifold
corresponds to an ellipse in the image. The parameter space becomes a Riemannian manifold under a Fisher-Rao metric, which
is derived from a Gaussian model for the blurring of ellipses in the image. Two points in the parameter space are close together
under the Fisher-Rao metric if the corresponding ellipses are close together in the image. The Fisher-Rao metric is accurately
approximated by a simpler metric under the assumption that the blurring is small compared with the sizes of the ellipses under
consideration. It is shown that the parameter space for the ellipses in the image has a finite volume under the approximation
to the Fisher-Rao metric. As a consequence the parameter space can be replaced, for the purpose of ellipse detection, by a
finite set of points sampled from it. An efficient algorithm for sampling the parameter space is described. The algorithm
uses the fact that the approximating metric is flat, and therefore locally Euclidean, on each three dimensional family of
ellipses with a fixed orientation and a fixed eccentricity. Once the sample points have been obtained, ellipses are detected
in a given image by checking each sample point in turn to see if the corresponding ellipse is supported by the nearby image
pixel values. The resulting algorithm for ellipse detection is implemented. A multiresolution version of the algorithm is
also implemented. The experimental results suggest that ellipses can be reliably detected in a given low resolution image
and that the number of false detections can be reduced using the multiresolution algorithm. 相似文献
2.
The iterated prisoners dilemma (IPD) is a simple model for the study of the emergence of cooperative behavior in populations
of selfish individuals. In this work, we challenge the assumption that players move in synchrony, and develop a general Markovian
model that allows the study of a wide spectrum of scenarios. Simulations show that the relative timing of player moves, and
the reward for mutual cooperation, influences the strategy that eventually dominates the final population. For a synchronous
environment, reciprocal behavior appears to be the key to the evolution of cooperation, while in an asynchronous environment,
guarded generosity may be a route to the evolution of cooperation. 相似文献