Vol-1539⫷ Vol-1540 ⫸Vol-1541
urn:nbn:de:0074-1540-0

Copyright © 2015 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

MuSRobS 2015
Multimodal and Semantics for Robotics Systems

Proceedings of the Workshop on Multimodal and Semantics for Robotics Systems (MuSRobS)
co-located with IEEE/RSJ International Conference on Intelligent Robots and Systems ( IROS2015 )

Hamburg, Germany, October 1, 2015 .

Edited by

Marco A. Gutierrez ^{1, 2}
Rafael E. Banchs ²
Suraj Nair ³

¹ Robotics and Artificial Vision Laboratory (Robolab) , Polytechnic School, University of Extremadura Avda. de la Universidad s/n, 10003, Cáceres, Spain
² Human Language Technology Dpt. , Institute for Infocomm Research, A*STAR, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632
³ TUM Arcisstraße 21, 80333 München, Germany & TUM Create , 1 Create Way #10-02 Create Tower, Singapore 138602

Table of Contents

MuSRobS 2015 Technical Papers

A Novel Multimodal Emotion Recognition Approach for Affective Human Robot Interaction 1-9
Felipe Cid, Luis J. Manso, Pedro Núñez
A Multi-modal Approach for Assistive Humanoid Robots 10-15
German I. Parisi, Johannes Bauer, Erik Strahl, Stefan Wermter
An Intelligent Application Development Platform for Service Robots 16-20
Y. Sugawara, T. Morita, S. Saito, T. Yamaguchi
Multimodal Binding of Parameters for Task-based Robot Programming Based on Semantic Descriptions of Modalities and Parameter Types 21-24
Alexander Perzylo, Nikhil Somani, Stefan Profanter, Markus Rickert, Alois Knoll
Connecting Natural Language to Task Demonstrations and Low-level Control of Industrial Robots 25-29
Maj Stenmark, Jacek Malec
Perceptive Parallel Processes Coordinating Geometry and Texture 30-35
Marco A. Gutierrez, Rafael E. Banchs, Luis F. D'Haro

MuSRobS Extended Abstracts from Invited Speakers

NVIDIA Jetson for Embedded, How high-performance and low-energy computing systems for deep learning and computer vision can help Robotics. 36-37
Serge Palaric
Robotic Vision: Understanding Improves the Geometric Accuracy 38-39
Javier Civera
SP1: Stereo Vision in Real Time 40-41
Konstantin Schauwecker

2015-10-24: submitted by Marco A. Gutierrez, metadata incl. bibliographic data published under Creative Commons CC0
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