Publikation
Multisensor-Pipeline: A Lightweight, Flexible, and Extensible Framework for Building Multimodal-Multisensor Interfaces
Michael Barz; Omair Shahzad Bhatti; Bengt Lüers; Alexander Prange; Daniel Sonntag
In: Companion Publication of the 2021 International Conference on Multimodal Interaction. ACM International Conference on Multimodal Interaction (ICMI-2021), October 18-22, Montréal, QC, Canada, Pages 13-18, ISBN 9781450384711, Association for Computing Machinery, New York, NY, USA, 2021.
Zusammenfassung
We present the multisensor-pipeline (MSP), a lightweight, flexible, and extensible framework for prototyping multimodal-multisensor
interfaces based on real-time sensor input. Our open-source framework (available on GitHub) enables researchers and developers
to easily integrate multiple sensors or other data streams via source modules, to add stream and event processing capabilities via
processor modules, and to connect user interfaces or databases via sink modules in a graph-based processing pipeline. Our framework
is implemented in Python with a low number of dependencies, which enables a quick setup process, execution across multiple operating
systems, and direct access to cutting-edge machine learning libraries and models. We showcase the functionality and capabilities of
MSP through a sample application that connects a mobile eye tracker to classify image patches surrounding the user’s fixation points
and visualizes the classification results in real-time.
Projekte
GeAR - Gelingensbedingungen und Grundsatzfragen von Augmented Reality in experimentellen Lehr-Lernszenarien,
SciBot - Data Science Chatbot: Eine Textbasierte Schnittstelle, die von Experten lernt, um Experten zu unterstützen
SciBot - Data Science Chatbot: Eine Textbasierte Schnittstelle, die von Experten lernt, um Experten zu unterstützen