196,167 research outputs found
ToBI - Team of Bielefeld: The Human-Robot Interaction System for RoboCup@Home 2009
No full textWachsmuth S, Hanheide M, Siepmann F, Spexard T. ToBI - Team of Bielefeld: The Human-Robot Interaction System for RoboCup@Home 2009. Graz, Austria; 2009.The ToBI robocup team has been newly founded in Jan 2009 in order to proceed existing long-term research in the development of robot companions for domestic environments towards new challenges in more standardized benchmarking procedures, like RoboCup@Home. The main features of the ToBI system are a flexibile Active Memory-based architecture that enables the fast integration of new processing modules and new system behaviors and the modeling of mixed-initiative strategies for multi-modal dialog. The overall goal is an out-of-the-box robot that is able to successfully interact with na¨
ıve users. In this paper we describe the technical basis on which the ToBI system is based and give some insights on previous evaluation experiences
Facial Communicative Signal Interpretation in Human-Robot Interaction by Discriminative Video Subsequence Selection
No full textLang C, Wachsmuth S, Hanheide M, Wersing H. Facial Communicative Signal Interpretation in Human-Robot Interaction by Discriminative Video Subsequence Selection.; 2012.Facial communicative signals (FCSs) such as head gestures, eye gaze, and facial expressions can provide useful feedback in conversations between people and also in human-robot interaction. This paper presents a pattern recognition approach for the interpretation of FCSs in terms of valence, based on the selection of discriminative subsequences in video data. These subsequences capture important temporal dynamics and are used as prototypical reference subsequences in a classification procedure based on dynamic time warping and feature extraction with active appearance models. The approach is evaluated on a database containing videos of people interacting with a robot by teaching the names of several objects to it. The verbal answer of the robot is expected to elicit the display of spontaneous FCSs by the human tutor, which were classified in this work. The achieved classification rates are comparable to the average human recognition performance and outperformed our previous results on this task
Enhancing Human Cooperation with Multimodal Augmented Reality
No full textMertes C, Dierker A, Hermann T, Hanheide M, Sagerer G. Enhancing Human Cooperation with Multimodal Augmented Reality. In: Proceedings of the 13th International Conference on Human-Computer Interaction. Lecture Notes in Computer Science, 5610-56. Heidelberg, Germany: Springer; 2009: 447-451.
Humans naturally use an impressive variety of ways to communicate. In this work, we investigate the possibilities of complementing these natural communication channels with artificial ones. For this, augmented reality is used as a technique to add synthetic visual and auditory stimuli to people's perception. A system for the mutual display of the gaze direction of two interactants is presented and its acceptance is shown through a study. Finally, future possibilities of promoting this novel concept of artificial communication channels are explored
Fusion of perceptual processes for real-time object tracking
No full textJüngling K, Arens M, Hanheide M, Sagerer G. Fusion of perceptual processes for real-time object tracking. In: International Conference on Information Fusion. IEEE; 2008: 1-8
Moving from augmented to interactive mapping
No full textBooij O, Kröse B, Peltason J, Spexard T, Hanheide M. Moving from augmented to interactive mapping. In: Robotics: Science and Systems Conference. 2008
A cognitive ego-vision system for interactive assistance
No full textHanheide M. A cognitive ego-vision system for interactive assistance. Bielefeld (Germany): Bielefeld University; 2006.With increasing computational power and decreasing size, computers nowadays are already wearable and mobile. They become attendant of peoples' everyday life. Personal digital assistants and mobile phones equipped with adequate software gain a lot of interest in public, although the functionality they provide in terms of assistance is little more than a mobile databases for appointments, addresses, to-do lists and photos. Compared to the assistance a human can provide, such systems are hardly to call real assistants.
The motivation to construct more human-like assistance systems that develop a certain level of cognitive capabilities leads to the exploration of two central paradigms in this work. The first paradigm is termed cognitive vision systems. Such systems take human cognition as a design principle of underlying concepts and develop learning and adaptation capabilities to be more flexible in their application. They are embodied, active, and situated. Second, the ego-vision paradigm is introduced as a very tight interaction scheme between a user and a computer system that especially eases close collaboration and assistance between these two. Ego-vision systems (EVS) take a user's (visual) perspective and integrate the human in the system's processing loop by means of a shared perception and augmented reality. EVSs adopt techniques of cognitive vision to identify objects, interpret actions, and understand the user's visual perception. And they articulate their knowledge and interpretation by means of augmentations of the user's own view.
These two paradigms are studied as rather general concepts, but always with the goal in mind to realize more flexible assistance systems that closely collaborate with its users. This work provides three major contributions. First, a definition and explanation of ego-vision as a novel paradigm is given. Benefits and challenges of this paradigm are discussed as well. Second, a configuration of different approaches that permit an ego-vision system to perceive its environment and its user is presented in terms of object and action recognition, head gesture recognition, and mosaicing. These account for the specific challenges identified for ego-vision systems, whose perception capabilities are based on wearable sensors only. Finally, a visual active memory (VAM) is introduced as a flexible conceptual architecture for cognitive vision systems in general, and for assistance systems in particular. It adopts principles of human cognition to develop a representation for information stored in this memory. So-called memory processes continuously analyze, modify, and extend the content of this VAM. The functionality of the integrated system emerges from their coordinated interplay of these memory processes.
An integrated assistance system applying the approaches and concepts outlined before is implemented on the basis of the visual active memory. The system architecture is discussed and some exemplary processing paths in this system are presented and discussed. It assists users in object manipulation tasks and has reached a maturity level that allows to conduct user studies. Quantitative results of different integrated memory processes are as well presented as an assessment of the interactive system by means of these user studies
A Probabilistic Model for Self-Awareness in an Event-Based Intelligent System
No full textGolombek R, Wrede S, Hanheide M. A Probabilistic Model for Self-Awareness in an Event-Based Intelligent System.; 2009
Analysis of human-robot spatial behaviour applying a qualitative trajectory calculus
No full textThe analysis and understanding of human-robot joint spatial behaviour (JSB) - such as guiding, approaching, departing, or coordinating movements in narrow spaces - and its communicative and dynamic aspects are key requirements on the road towards more intuitive interaction, safe encounter, and appealing living with mobile robots. This endeavours demand for appropriate models and methodologies to represent JSB and facilitate its analysis. In this paper, we adopt a qualitative trajectory calculus (QTC) as a formal foundation for the analysis and representation of such spatial behaviour of a human and a robot based on a compact encoding of the relative trajectories of two interacting agents in a sequential model. We present this QTC together with a distance measure and a probabilistic behaviour model and outline its usage in an actual JSB study. We argue that the proposed QTC coding scheme and derived methodologies for analysis and modelling are flexible and extensible to be adapted for a variety of other scenarios and studies. © 2012 IEEE
Automatic Initialization for Facial Analysis in Interactive Robotics
No full textRabie A, Lang C, Hanheide M, Castrillon-Santana M, Sagerer G. Automatic Initialization for Facial Analysis in Interactive Robotics. In: International Conference on Computer Vision Systems. Lecture Notes in Computer Science ; 5008. Vol 5008. Berlin, Heidelberg: Springer; 2008: 517-526.The human face plays an important role in communication as it allows to discern different interaction partners and provides nonverbal feedback. In this paper, we present a soft real-time vision system that enables an interactive robot to analyze faces of interaction partners not only to identify them, but also to recognize their respective facial expressions as a dialog-controlling non-verbal cue. In order to assure applicability in real world environments, a robust detection scheme is presented which detects faces and basic facial features such as the position of the mouth, nose, and eyes. Based on these detected features, facial parameters are extracted using active appearance models (AAMs) and conveyed to support vector machine (SVM) classifiers to identify both persons and facial expressions. This paper focuses on four different initialization methods for determining the initial shape for the AAM algorithm and their particular performance in two different classification tasks with respect to either the facial expression DaFEx database and to the real world data obtained from a robot’s point of view
Remembering interaction episodes: an unsupervised learning approach for a humanoid robot
No full textGieselmann S, Hanheide M, Wrede B. Remembering interaction episodes: an unsupervised learning approach for a humanoid robot. In: Humanoids 2010. Nashville/Tennessee; 2010
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