The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of threedimensional models when an initial relative pose estimate is available. The ba...
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of computing two of the most basic spatio-temporal patterns in...
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
We formulate contour correspondence as a Quadratic Assignment Problem (QAP), incorporating proximity information. By maintaining the neighborhood relation between points this way,...
Oliver van Kaick, Ghassan Hamarneh, Hao Zhang 0002...
We propose an algorithm that groups points similarly to how human observers do. It is simple, totally unsupervised and able to find clusters of complex and not necessarily convex s...