Text Density and Display Bandwidth: Evaluating Scalability by Model and Experiment
Title | Text Density and Display Bandwidth: Evaluating Scalability by Model and Experiment |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Iyer, Jagathshree, Polys, Nicholas F., Arsenault, Lance |
Conference Name | Proceedings of the 22Nd International Conference on 3D Web Technology |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-4955-0 |
Keywords | 3D, composability, density, Human Behavior, human factors, Metrics, pubcrawl, Scalability, Text, text analytics, user interface, visual analytics |
Abstract | The applications of 3D Virtual Environments are taking giant leaps with more sophisticated 3D user interfaces and immersive technologies. Interactive 3D and Virtual Reality platforms present a great opportunity for data analytics and can represent large amounts of data to help humans in decision making and insight. For any of the above to be effective, it is essential to understand the characteristics of these interfaces in displaying different types of content. Text is an essential and widespread content and legibility acts as an important criterion to determine the style, size and quantity of the text to be displayed. This study evaluates the maximum amount of text per visual angle, that is, the maximum density of text that will be legible in a virtual environment displayed on different platforms. We used Extensible 3D (X3D) to provide the portable (cross-platform) stimuli. The results presented here are based on a user study conducted in DeepSix (a tiled LCD display with 5750x2400 resolution) and the Hypercube (an immersive CAVE-style active stereo projection system with three walls and floor at 2560x2560 pixels active stereo per wall). We found that more legible text can be displayed on an immersive projection due to its larger Field of Regard; in the immersive case, stereo versus monoscopic rendering did not have a significant effect on legibility. |
URL | https://dl.acm.org/citation.cfm?doid=3055624.3075958 |
DOI | 10.1145/3055624.3075958 |
Citation Key | iyer_text_2017 |