R.C. Hoover (USA)
Manifold learning, appearance manifolds, curvature.
The current paper develops methods to analyze the local and global characteristics of one-dimensional manifolds arising in applications of pose determination in robotic vision. The approach for local analysis utilizes techniques from differential geometry to construct local coordinate frames in the high-dimensional image space. These frames provide analytical information about the local geometry of the manifold. For global analysis a distance matrix is developed to analyze how “irregular” the manifold is. Experimental results are provided by applying the proposed approach on both synthetic one-manifolds as well as one manifolds generated by real image data.
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