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Gerhard Sagerer

Researcher at Bielefeld University

Publications -  281
Citations -  5817

Gerhard Sagerer is an academic researcher from Bielefeld University. The author has contributed to research in topics: Mobile robot & Social robot. The author has an hindex of 37, co-authored 281 publications receiving 5585 citations. Previous affiliations of Gerhard Sagerer include University of Erlangen-Nuremberg & Daimler AG.

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Proceedings Article

Enhancing human cooperation with multimodal augmented reality

TL;DR: This work investigates the possibilities of complementing these natural communication channels with artificial ones using augmented reality as a technique to add synthetic visual and auditory stimuli to people's perception.
Proceedings Article

ElMaR: A Protein Docking System using Flexibility Information

TL;DR: An overview of the ElMaR Docking System is given, which incorporates protein flexibility obtained through statistics and force field calculation and weights steric clash penalties according to the possibility of amino acid rotamer changes.
Proceedings Article

A HMM-based recognition system for perceptive relevant pitch movements of spontaneous German speech.

TL;DR: An HMM-based recognition system for perceptive relevant pitch movements of spontaneous German speech based on a hybrid approach combining polynomial classi cation with Hidden Markov Modelling.
Proceedings Article

Theory of Mind (ToM) on Robots: A Neuroimaging Study

TL;DR: In this article, the authors present the preliminary results of an fMRI-study in which participants had to play a version of the classical Prisoners' Dilemma Game (PDG) against four opponents: a human partner (HP), an anthropomorphic robot (AR), a functional robot (FR), and a computer (CP).
Proceedings Article

Robust Interpretation of Speech

TL;DR: This work proposes an appropriate criterion and shows how the requirements for robust interpretation of speech can be met in a dialog system and how this criterion has to be applied when the analysis has produced the best results obtainable from the input data.