Name
Title | ||
|---|---|---|
Display methods of projection augmented reality based on deep learning pose estimation |
Abstract | ||
|---|---|---|
In this paper, we propose three display methods for projection-based augmented reality. In spatial augmented reality (SAR), determining where information, objects, or contents are to be displayed is a difficult and important issue. We use deep learning models to estimate user pose and suggest ways to solve the issue based on this data. Finally, each method can be appropriately applied according to various the applications and scenarios.
|
Year | DOI | Keywords |
|---|---|---|
2019 | 10.1145/3306214.3338608 | deep learning, mixed reality, pose estimation, projection augmented reality, spatial augmented reality |
Field | DocType | ISSN |
Computer vision,Computer graphics (images),Computer science,Augmented reality,Pose,Artificial intelligence,Deep learning | Conference | 978-1-4503-6314-3 |
ISBN | Citations | PageRank |
978-1-4503-6314-3 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyocheol Ro | 1 | 0 | 3.72 |
| Yoon Jung Park | 2 | 1 | 2.04 |
| Junghyun Byun | 3 | 0 | 3.04 |
| Tack-Don Han | 4 | 351 | 66.39 |