Probabilistic Generative Modelling
نویسندگان
چکیده
The contribution of this paper is the adaption of data driven methods for decomposition of tangent shape variability proposed in a probabilistic framework. By Bayesian model selection we compare two generative model representations derived by principal components analysis and by maximum autocorrelation factors analysis.
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تاریخ انتشار 2003