Analysis of the co-design activity: influence of a mixed artifact and contribution of the gestural function in a spatial augmented reality environment
November 15, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Maud Poulin, Jean-FranΓ§ois Boujut, CΓ©dric Masclet
arXiv ID
1911.07985
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Augmented reality provides new possibilities to propose environments where the designers can take advantage of the physicality of the artifacts while keeping the versatility of digital environments. Mixed objects can therefore provide new media in the interactions between stakeholders. Besides, the increasing interest in user participation in early design phases is limited by the poor representations or the expensive mock ups to be provided in design meetings. Therefore, understanding the role of these mixed artifacts by analyzing and characterizing the interactions is crucial to the development of both design methods and environments. By focusing on multimodal interactions, we aim at providing new results in terms of the design process, in particular by studying the contribution of the gesture in collaborative product co-creativity sessions but also by understanding the role of these multiple interactions in an augmented reality environment.
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