This paper investigates the design of a system for recognizing
objects in 3D point clouds of urban environments.
The system is decomposed into four steps: locating, segmenting,
...
Aleksey Golovinskiy, Vladimir G. Kim, Thomas Funkh...
The Error Correcting Output Coding (ECOC) approach to classifier design decomposes a multi-class problem into a set of complementary two-class problems. We show how to apply the E...
Josef Kittler, Reza Ghaderi, Terry Windeatt, Jiri ...
We consider the problem of clustering data lying on multiple subspaces of unknown and possibly different dimensions. We show that one can represent the subspaces with a set of pol...
This paper presents a novel and efficient algorithm for the 3D range to 2D image registration problem in urban scene settings. Our input is a set of unregistered 3D range scans an...
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...