Gerda Kamberova

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In this paper we address an application of computer vision which can in the future change completely our way of communicating over the network. We present our version of a testbed for telecollaboration. It is based on a highly accurate and precise stereo algorithm. The results demonstrate the live (on-line) recovery of 3D models of a dynamically changing(More)
We present a new method for defining neighborhoods, and assigning principal curvature frames, and mean and Gauss curvatures to the points of an unorganized oriented point-cloud. The neighborhoods are estimated by measuring implicitly the surface distance between points. The 3D shape recovery is based on conformal geometry, works directly on the cloud, does(More)
We evaluate our recently developed conformal method for quantitative shape extraction from unorganized 3D oriented point clouds. The conformal method has been tested previously on real, noisy, 3D data. Here we focus on the empirical evaluation of its performance on synthetic, ground truth data, and comparisons with other methods for quantitative extraction(More)
– Creativity and innovativeness are among the most essential attributes of engineering graduates and also of successful entrepreneurs. Entrepreneurship, or the process of starting a new venture, is one of the main roads to new technological innovations. This paper presents two novel models of entrepreneurship education integrated in computer science and(More)
A new technique for computing the differential invariants of a surface from 3D sample points and normals. It is based on a new conformal geometric approach to computing shape invariants directly from the Gauss map. In the current implementation we compute the mean curvature, the Gauss curvature, and the principal curvature axes at 3D points reconstructed by(More)