Combining tactile and tangible input for 3D selection
| Autor: | Lonni Besançon, Tobias Isenberg, Mehdi Ammi, Mickael Sereno |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry Scientific visualization 020207 software engineering 02 engineering and technology Machine learning computer.software_genre Task (project management) 3d space Control theory 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Spatial analysis computer Selection (genetic algorithm) |
| Zdroj: | IHM |
| DOI: | 10.1145/3132129.3132150 |
| Popis: | We present the design of a 6-DOF tangible controller for 3D spatial data selection. Such selection is a fundamental task in scientific visualization : it is performed prior to many other interactions. Many datasets are defined in 3D space, yet selection is often performed based on 2D input. While 2D-input-based selection may be efficient for datasets with explicit shapes, it is less efficient for data without such objects or structures. We then address this issue by combining 2D tactile with 3D tangible input to perform 3D selection in volumetric datasets. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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