Mixture Model for Image Understanding and the Em Algorithm
نویسنده
چکیده
We present a mixture model that can be applied to the recognition of multiple objects in an image plane. The model consists of any shape of submodules. Each submodule is a probability density function of data points with scale and shift parameters, and the modules are combined with weight probabilities. We present the EM (Expectation-Maximization) algorithm to estimate those parameters. We also modify the algorithm in the case that data points are restricted in an attention window. Mathematical Informatics Section
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تاریخ انتشار 1995