220 research outputs found
From images via symbols to contexts: using augmented reality for interactive model acquisition
Systems that perform in real environments need to bind the internal state to externally
perceived objects, events, or complete scenes. How to learn this correspondence has been a long
standing problem in computer vision as well as artificial intelligence. Augmented Reality provides
an interesting perspective on this problem because a human user can directly relate displayed
system results to real environments. In the following we present a system that is able to bootstrap
internal models from user-system interactions. Starting from pictorial representations it learns
symbolic object labels that provide the basis for storing observed episodes. In a second step, more
complex relational information is extracted from stored episodes that enables the system to react
on specific scene contexts
Active vision-based localization for robots in a home-tour scenario
Self-Localization is a crucial task for mobile robots. It is not only a requirement
for auto navigation but also provides contextual information to support
human robot interaction (HRI). In this paper we present an active vision-based
localization method for integration in a complex robot system to work in human
interaction scenarios (e.g. home-tour) in a real world apartment. The holistic
features used are robust to illumination and structural changes in the scene. The
system uses only a single pan-tilt camera shared between different vision applications
running in parallel to reduce the number of sensors. Additional information
from other modalities (like laser scanners) can be used, profiting of an integration
into an existing system. The camera view can be actively adapted and the
evaluation showed that different rooms can be discerned
Towards Automated Execution and Evaluation of Simulated Prototype HRI Experiments
Lier F, Lütkebohle I, Wachsmuth S. Towards Automated Execution and Evaluation of Simulated Prototype HRI Experiments. In: HRI '14 Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction. New York, NY, USA: ACM; 2014: 230-231.Autonomous robots are highly relevant targets for interaction studies, but can exhibit behavioral variability that confounds experimental validity. Currently, testing on real systems is the only means to prevent this, but remains very labour-intensive and often happens too late. To improve this situation, we are working towards early testing by means of partial simulation, with automated assessment, and based upon continuous software integration to prevent regressions. We will introduce the concept and describe a proof-of-concept that demonstrates fast feedback and coherent experiment results across repeated trials
Direct On-Line Imitation of Human Faces with Hierarchical ART Networks
Holthaus P, Wachsmuth S. Direct On-Line Imitation of Human Faces with Hierarchical ART Networks. In: 2013 IEEE RO-MAN. The 22nd International Symposium on Robot and Human Interactive Communication. Piscataway, NJ: IEEE; 2013: 370-371.This work-in-progress paper presents an on-line system for robotic heads capable of mimicking humans. The marker-less method solely depends on the interactant’s face as an input and does not use a set of basic emotions and is thus capable of displaying a large variety of facial expressions. A preliminary evaluation assigns solid performance with potential for improvement
Integration and coordination in a cognitive vision system
In this paper, we present a case study that exemplifies
general ideas of system integration and coordination.
The application field of assistant technology provides an
ideal test bed for complex computer vision systems including
real-time components, human-computer interaction, dynamic
3-d environments, and information retrieval aspects.
In our scenario the user is wearing an augmented reality device
that supports her/him in everyday tasks by presenting
information that is triggered by perceptual and contextual
cues. The system integrates a wide variety of visual functions
like localization, object tracking and recognition, action
recognition, interactive object learning, etc. We show
how different kinds of system behavior are realized using
the Active Memory Infrastructure that provides the technical
basis for distributed computation and a data- and eventdriven
integration approach
Modeling Software Systems in Experimental Robotics for Improved Reproducibility -- A Case Study with the iCub Humanoid Robot
Lier F, Wachsmuth S, Wrede S. Modeling Software Systems in Experimental Robotics for Improved Reproducibility -- A Case Study with the iCub Humanoid Robot. Presented at the IEEE-RAS International Conference on Humanoid Robots, Madrid, Spain
Mensch-Maschine-Interaktion
Wachsmuth I. Mensch-Maschine-Interaktion. In: Stephan A, Walter S, eds. Handbuch Kognitionswissenschaft. Stuttgart Weimar: J.B. Metzler; 2013: 361-364
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