Intelligent agents are often called upon to form plans that direct their own or other agents’ activities. For these systems, the ability to describe plans to people in natural ways is an essential aspect of their interface. In this paper, we present the Cooperative Plan Identification (CPI) architecture, a computational model that generates concise, effective textual descriptions of plan data s...

The literature on recursive estimation of structure and motion from monocular image sequences comprises a large number of apparently unrelated models and estimation techniques. We propose a framework that allows us to derive and compare all models by following the idea of dynamical system reduction. The “natural” dynamic model, derived from the rigidity constraint and the projection model, is f...

This chapter deals with fundamental methods as well as current research on physics-based human gait analysis. We present valuable concepts that allow efficient modeling of the kinematics and the dynamics of the human body. The resulting physical model can be included in an optimization-based framework. In this context, we show how forward dynamics optimization can be used to determine the produ...

When a plan involves hundreds or thousands of events over time it can be di cult or impossible to tell whether those events are unfolding \according to plan" and to assess the impact of dynamic plan modi cations. Pathological states may arise in which goals cannot be attained or are attained too slowly. Plan steering is an agent-based approach to this problem. The agent monitors an unfolding pl...

From perspective of energy security, this study focuses on oil-importing optimal decision based on multi-objective programming approach. Different from other models, country risk is considered as the main objective to minimize risk exposure of importing disruption. What is more, this model connects emergency management with programming, and optimal decisions are solved under different scenarios...

In animal models of depression, depression is defined as performance on a learning task. That task is typically escaping a mild electric shock in a shuttle cage by moving from one side of the cage to the other. Ovarian hormones influence learning in other kinds of tasks, and these hormones are associated with depressive symptoms in humans. The role of these hormones in shuttle-cage escape learn...

This paper describes a visual markerless real-time tracking system for Augmented Reality applications. The system uses a firewire camera with a fisheye lens mounted at 10 fps. Visual tracking of 3D scene points is performed simultaneously with 3D camera pose estimation without any prior scene knowledge. All visual-geometric data is acquired using a structure-from-motion approach. The lens selec...

Our participation in TREC 2003 aims to adapt the use of the DFR (Divergence From Randomness) models with Query Expansion (QE) to the robust track and the topic distillation task of the Web track. We focus on the robust track, where the utilization of QE improves the global performance but hurts the performance on the worst topics. In particular, we study the problem of the selective application...

We present a processing technique for a robust reconstruction of motion properties for single points in large scale, dynamic environments. We assume that the acquisition camera is moving and that there are other independently moving agents in a large environment, like road scenarios. The separation of direction and magnitude of the reconstructed motion allows for robust reconstruction of the dy...

The identification and description of partial symmetries in man-made structures is a powerful tool to improve the quality of 3D reconstruction from unordered images and to enable high-level understanding of scene geometry. In this work we propose an approach to identify symmetries and exploit them in Structure from Motion (SfM). Our first contribution is a symmetry detection approach that uses ...