Cargando…
Automating Areas of Interest Analysis in Mobile Eye Tracking Experiments based on Machine Learning
For an in-depth, AOI-based analysis of mobile eye tracking data, a preceding gaze assign-ment step is inevitable. Current solutions such as manual gaze mapping or marker-based approaches are tedious and not suitable for applications manipulating tangible objects. This makes mobile eye tracking studi...
Autores principales: | Wolf, Julian, Hess, Stephan, Bachmann, David, Lohmeyer, Quentin, Meboldt, Mirko |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bern Open Publishing
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909988/ https://www.ncbi.nlm.nih.gov/pubmed/33828716 http://dx.doi.org/10.16910/jemr.11.6.6 |
Ejemplares similares
-
Measuring teamwork for training in healthcare using eye tracking and pose estimation
por: Weiss, Kerrin Elisabeth, et al.
Publicado: (2023) -
Value of Eye-Tracking Data for Classification of Information Processing–Intensive Handling Tasks: Quasi-Experimental Study on Cognition and User Interface Design
por: Wegner, Stephan, et al.
Publicado: (2020) -
Eye Tracking Supported Human Factors Testing Improving Patient Training
por: Weiss, Kerrin Elisabeth, et al.
Publicado: (2021) -
Object-Gaze Distance: Quantifying Near- Peripheral Gaze Behavior in Real-World Applications
por: Wang, Felix S., et al.
Publicado: (2021) -
Comparing the effectiveness of augmented reality-based and conventional instructions during single ECMO cannulation training
por: Wolf, Julian, et al.
Publicado: (2021)