Nonlinear Shape-Texture Manifold Learning
نویسندگان
چکیده
منابع مشابه
Nonlinear manifold learning for dynamic shape and dynamic appearance
Our objective is to learn representations for the shape and the appearance of moving (dynamic) objects that support tasks such as synthesis, pose recovery, reconstruction, and tracking. In this paper, we introduce a framework that aim to learn a landmark-free correspondence-free global representations of dynamic appearance manifolds. We use nonlinear dimensionality reduction to achieve an embed...
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Manifold learning is the process of estimating a low-dimensional structure which underlies a collection of high-dimensional data. Here we review two popular methods for nonlinear dimensionality reduction, locally linear embedding (LLE, [1]) and IsoMap [2]. We also discuss their roots in principal component analysis and multidimensional scaling, and provide a brief comparison of the underlying a...
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ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2010
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.e93.d.2016