This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. ...
A general framework for automatic 3D soccer ball estimation and tracking from multiple image sequences is proposed. Firstly, the ball trajectory is modelled as planarcurves in con...
Jinchang Ren, James Orwell, Graeme A. Jones, Ming ...
We develop an approach to intrinsic dimension estimation based on k-nearest neighbor (kNN) distances. The dimension estimator is derived using a general theory on functionals of k...