C-D Ratio in multi-display environments
February 12, 2020 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Travis Gesslein, Jens Grubert
arXiv ID
2002.04980
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Research in user interaction with mixed reality environments using multiple displays has become increasingly relevant with the prevalence of mobile devices in everyday life and increased commoditization of large display area technologies using projectors or large displays. Previous work often combines touch-based input with other approaches, such as gesture-based input, to expand the possible interaction space or deal with limitations of other two-dimensional input methods. In contrast to previous methods, we examine the possibilities when the control-display (C-D) ratio is significantly smaller than one and small input movements result in large output movements. To this end one specific multi-display configuration is implemented in the form of a spatial-augmented reality sandbox environment, and used to explore various interaction techniques based on a variety of mobile device touch-based input and optical marker tracking-based finger input. A small pilot study determines the most promising input candidate, which is compared to traditional touch-input based techniques in a user study that tests it for practical relevance. Results and conclusions of the study are presented.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted