In this paper we present the core of LoCo, a logic-based high-level representation language for expressing configuration problems. LoCo shall allow to model these problems in an intuitive and declarative way, the dynamic aspects of configuration notwithstanding. Our logic enforces that configurations contain only finitely many components and reasoning can be reduced to the task of model constru...

In order to apply advanced high-level concepts for transportation networks, like hypergraphs, multi-level wayfinding and traffic forecasting, to commercially available street network datasets, it is often necessary to generalise from network primitives. However, the appropriate method of generalisation strongly depends on the complex street network feature they belong to. In this paper, we deve...

We present an approach for recognizing human walking movements using low-level motion regularities and constraints. Biomechanical features for classification are automatically extracted from video sequences of walkers. A multiplicative classification rule using statistical distances is then used to determine whether an unknown motion is consistent with normal walking patterns. Recognition resul...

  Background: The breeding performance is an important parameter to evaluate the breeding success in captive condition. The optimum hormone dose in combination with latency period is desirable for getting best breeding performance in fish. Objectives: <span style="color: win...

The left ventricle tracking in planar scintigraphic images is an important step to study the coronary state. However, it is not as simple as we thought, because of the bad quality of these images. The study of the related work showed that classic methods based on low level image characteristics failed to localize the ventricle. In this paper, we suggest using a method based on a priori knowledg...

Anatomical shape variations are typically difficult to model and parametric or hand-crafted models can lead to ill-fitting segmentations. This difficulty can be addressed with a framework like autocontext, that learns to jointly detect and regularize a segmentation. However, mis-segmentation can still occur when a desired structure, such as the spinal cord, has few locally distinct features. Hi...