Georg Layher
Georg Layher
Institute of Neural Information Processing, Ulm University
Verified email at
Cited by
Cited by
Fully Convolutional Region Proposal Networks for Multispectral Person Detection
D König, M Adam, C Jarvers, G Layher, H Neumann, M Teutsch
Computer Vision and Pattern Recognition Workshops (CVPRW), 2017 IEEE …, 2017
Multiple classifier systems for the classification of audio-visual emotional states
M Glodek, S Tschechne, G Layher, M Schels, T Brosch, S Scherer, ...
Affective Computing and Intelligent Interaction, 359-368, 2011
The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain-and Emotion-Recognition System
M Velana, S Gruss, G Layher, P Thiam, Y Zhang, D Schork, V Kessler, ...
IAPR Workshop on Multimodal Pattern Recognition of Social Signals in Human …, 2016
A comprehensive head pose and gaze database
U Weidenbacher, G Layher, PM Strauss, H Neumann
IET Digital Library, 2007
A generic framework for the inference of user states in human computer interaction
S Scherer, M Glodek, G Layher, M Schels, M Schmidt, T Brosch, ...
Journal on Multimodal User Interfaces 6 (3-4), 117-141, 2012
An audiovisual political speech analysis incorporating eye-tracking and perception data.
S Scherer, G Layher, J Kane, H Neumann, N Campbell
LREC, 1114-1120, 2012
Detection of head pose and gaze direction for human-computer interaction
U Weidenbacher, G Layher, P Bayerl, H Neumann
International Tutorial and Research Workshop on Perception and Interactive …, 2006
Multi-modal classifier-fusion for the recognition of emotions
M Schels, M Glodek, S Meudt, S Scherer, M Schmidt, G Layher, ...
Coverbal Synchrony in Human-Machine Interaction, 73-98, 2013
Learning representations of animated motion sequences—A neural model
G Layher, MA Giese, H Neumann
Topics in cognitive science 6 (1), 170-182, 2014
Embodied Learning of a Generative Neural Model for Biological Motion Perception and Inference
F Schrodt, G Layher, H Neumann, MV Butz
Frontiers in Computational Neuroscience 9, 79, 2015
Utilizing the Capabilities Offered by Eye-Tracking to Foster Novices’ Comprehension of Business Process Models
M Zimoch, R Pryss, G Layher, H Neumann, T Probst, W Schlee, ...
International Conference on Cognitive Computing, 155-163, 2018
Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning
V Riemer, J Frommel, G Layher, H Neumann, C Schrader
Frontiers in psychology 8, 1303, 2017
Real-time Biologically Inspired Action Recognition from Key Poses using a Neuromorphic Architecture
G Layher, T Brosch, H Neumann
Frontiers in Neurorobotics 11, 2017
Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement
G Layher, F Schrodt, MV Butz, H Neumann
Frontiers in psychology 5, 1287, 2014
Recognizing human activities using a layered Markov architecture
M Glodek, G Layher, F Schwenker, G Palm
Artificial Neural Networks and Machine Learning–ICANN 2012, 677-684, 2012
Learning representations for animated motion sequence and implied motion recognition
G Layher, MA Giese, H Neumann
Artificial Neural Networks and Machine Learning–ICANN 2012, 288-295, 2012
Modeling perspective-taking upon observation of 3D biological motion
F Schrodt, G Layher, H Neumann, MV Butz
Development and Learning and Epigenetic Robotics (ICDL-Epirob), 2014 Joint …, 2014
Robust stereoscopic head pose estimation in human-computer interaction and a unified evaluation framework
G Layher, H Liebau, R Niese, A Al-Hamadi, B Michaelis, H Neumann
International Conference on Image Analysis and Processing, 227-236, 2011
uulmMAD–A Human Action Recognition Dataset for Ground-Truth Evaluation and Investigation of View Invariances
M Glodek, G Layher, F Heilemann, F Gawrilowicz, G Palm, F Schwenker, ...
Multimodal Pattern Recognition of Social Signals in Human-Computer …, 2015
Modeling perspective-taking by correlating visual and proprioceptive dynamics
F Schrodt, G Layher, H Neumann, MV Butz
Proceedings fo the 36th Annual Conference of the Cognitive Science Society, 2014
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