Abstract. Clustering algorithms for multidimensional numerical data must overcome special difficulties due to the irregularities of data distribution. We present a clustering algo...
Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gaussians. Here we summarize these results and ...
This paper investigates the homography which transforms a set of points in projective space when undergoing a rigid translation, termed a projective translation. A representation ...
In this paper, we consider the problem of projective reconstruction based on the subspace method. Unlike existing subspace methods which require that all the points are visible in...
The robust regression techniques in the RANSAC family are popular today in computer vision, but their performance depends on a user supplied threshold. We eliminate this drawback ...