Refine
Departments, institutes and facilities
- Fachbereich Informatik (606)
- Fachbereich Ingenieurwissenschaften und Kommunikation (235)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (216)
- Institute of Visual Computing (IVC) (210)
- Institut für Cyber Security & Privacy (ICSP) (201)
- Fachbereich Wirtschaftswissenschaften (148)
- Institut für Verbraucherinformatik (IVI) (134)
- Fachbereich Angewandte Naturwissenschaften (76)
- Institut für funktionale Gen-Analytik (IFGA) (56)
- Internationales Zentrum für Nachhaltige Entwicklung (IZNE) (54)
Document Type
- Conference Object (1806) (remove)
Year of publication
Keywords
- FPGA (11)
- Machine Learning (9)
- Usable Security (9)
- Virtual Reality (9)
- Privacy (8)
- Robotics (7)
- Sustainability (7)
- DPA (6)
- Education (6)
- Entrepreneurship (6)
Traffic simulations are generally used to forecast traffic behavior or to simulate non-player characters in computer games and virual environments. These systems are usually modeled in such a way that traffic rules are strictly followed. However, rule violations are a common part of real-life traffic and thus should be integrated into such models.
Perception is one of the most important cognitive capabilities of an entity since it determines how an entity perceives its environment. The presented work focuses on providing cost efficient but realistic perceptual processes for intelligent virtual agents (IVAs) or NPCs with the goal of providing a sound information basis for the entities' decision making processes. In addition, an agent-central perception process should rovide a common interface for developers to retrieve data from the IVAs' environment. The overall process is evaluated by applying it to a scenario demonstrating its benefits. The evaluation indicates, that such a realistically simulated perception process provides a powerful instrument to enhance the (perceived) realism of an IVA's simulated behavior.
This paper describes a dynamic, model-based approach for estimating intensities of 22 out of 44 different basic facial muscle movements. These movements are defined as Action Units (AU) in the Facial Action Coding System (FACS) [1]. The maximum facial shape deformations that can be caused by the 22 AUs are represented as vectors in an anatomically based, deformable, point-based face model. The amount of deformation along these vectors represent the AU intensities, and its valid range is [0, 1]. An Extended Kalman Filter (EKF) with state constraints is used to estimate the AU intensities. The focus of this paper is on the modeling of constraints in order to impose the anatomically valid AU intensity range of [0, 1]. Two process models are considered, namely constant velocity and driven mass-spring-damper. The results show the temporal smoothing and disambiguation effect of the constrained EKF approach, when compared to the frame-by-frame model fitting approach ‘Regularized Landmark Mean-Shift (RLMS)’ [2]. This effect led to more than 35% increase in performance on a database of posed facial expressions.
Towards an Interaction-Centered and Dynamically Constructed Episodic Memory for Social Robots
(2020)
To provide seamless handoffs is an important task of cellular systems. A user of a real-time conversation on a mobile terminal should not notice when moving from one base station to another one. In this paper we address handoff procedures in a scenario where the radio access network is assumed to be IP-based, i.e., IP is used up to the base stations, and the mobile terminal runs a Mobile IP client. First we will motivate the need for differentiation of fast handoffs and seamless handoffs. Then we will survey some previously proposed micro-mobility extensions; thereby we will address the question of what degree of micro-mobility support is needed in the typical structure of a radio access network. The main part of this paper then discusses network-initiated/assisted handoffs in combination with Mobile IP. Here, we aim to bring together ideas of 2G/3G systems and of IP-based approaches.
Keeping planning problems as small as possible is a must in order to cope with complex tasks and environments. Earlier, we have described a method for cascading Description Logic (dl) representation and reasoning on the one hand, and Hierarchical Task Network (htn) action planning on the other. The planning domain description as well as the fundamental htn planning concepts are represented in dl and can therefore be subject to dl reasoning. From these representations, concise planning problems are generated for htn planners. We show by way of case study that this method yields significantly smaller planning problem descriptions than regular representations do in htn planning. The method is presented through a case study of a robot navigation domain and the blocks world domain. We present the benefits of using this approach in comparison with a pure htn planning approach.