Google Cardboard Dates Augmented Reality : Issues, Challenges and Future Opportunities
June 05, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ramakrishna Perla, Ramya Hebbalaguppe
arXiv ID
1706.03851
Category
cs.HC: Human-Computer Interaction
Citations
9
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The Google's frugal Cardboard solution for immersive Virtual Reality experiences has come a long way in the VR market. The Google Cardboard VR applications will support us in the fields such as education, virtual tourism, entertainment, gaming, design etc. Recently, Qualcomm's Vuforia SDK has introduced support for developing mixed reality applications for Google Cardboard which can combine Virtual and Augmented Reality to develop exciting and immersive experiences. In this work, we present a comprehensive review of Google Cardboard for AR and also highlight its technical and subjective limitations by conducting a feasibility study through the inspection of a Desktop computer use-case. Additionally, we recommend the future avenues for the Google Cardboard in AR. This work also serves as a guide for Android/iOS developers as there are no published scholarly articles or well documented studies exclusively on Google Cardboard with both user and developer's experience captured at one place.
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