We are proud to present the DAGM 2002 proceedings, which are the result of the e?orts of many people. First, there are the many authors, who have submitted so many excellent cont- butions. We received more than 140 papers, of which we could only accept about half in order not to overload the program. Only about one in seven submitted papers could be delivered as an oral presentation, for the same reason. But it needs to be said that almost all submissions were of a really high quality. This strong program could not have been put together without the support of the Program Committee. They took...
We are proud to present the DAGM 2002 proceedings, which are the result of the e?orts of many people. First, there are the many authors, who have subm...
3D Reconstruction from Multiple Images, Part 1: Principles discusses and explains methods to extract three-dimensional (3D) models from plain images. In particular, the 3D information is obtained from images for which the camera parameters are unknown. The principles underlying such uncalibrated structure-from-motion methods are outlined. First, a short review of 3D acquisition technologies puts such methods in a wider context and highlights their important advantages. Then, the actual theory behind this line of research is given. The authors have tried to keep the text maximally...
3D Reconstruction from Multiple Images, Part 1: Principles discusses and explains methods to extract three-dimensional (3D) models from plain images. ...
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to estimate the current state of the world. An implied assumption is that the future is stochastically similar to the past. The approach fails when the system encounters situations that are not anticipated from the past experience. In contrast, successful natural organisms identify new unanticipated stimuli and situations and frequently generate appropriate responses.
The observation described above lead...
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are l...
