High level methods for scene exploration

Virtual worlds exploration techniques are used in a wide variety of domains — from graph drawing to robot motion. This paper is dedicated to virtual world exploration techniques which have to help a human being to understand a 3D scene. An improved method of viewpoint quality estimation is presented in the paper, together with a new off-line method for automatic 3D scene exploration, based on a virtual camera. The automatic exploration method is working in two steps. In the first step, a set of “good” viewpoints is computed. The second step uses this set of points of view to compute a camera path around the scene. Finally, we define a notion of semantic distance between objects of the scene to improve the approach.

The Car Resequencing Problem with Pull-Off Tables

The car sequencing problem determines sequences of different car models launched down a mixed-model assembly line. To avoid work overloads of workforce, car sequencing restricts the maximum occurrence of labor-intensive options, e.g., a sunroof, by applying sequencing rules. We consider this problem in a resequencing context, where a given number of buffers (denoted as pull-off tables) is available for rearranging a stirred sequence. The problem is formalized and suited solution procedures are developed. A lower bound and a dominance rule are introduced which both reduce the running time of our graph approach. Finally, a real-world resequencing setting is investigated.