Tapestry is a platform for creating web-based applications that involve large volume rendering at scale. Tapestry uses Docker and the OSPRay renderer along with a scalable architecture to take scientific visualization to the web. For more information, you can check the Github page: https://github.com/seelabutk/tapestry
Photo-guided exploration of volumetric data features
Motivated by the power of deep neural networks, we posed the challenge of searching in volumetric data using sample target images/photographs. In this paper, we developed a technique to do just that using a genetic algorithm and a convolutional neural network.
Enchiladas is one of the components that drives the Tapestry project. It is a lightweight web-viewer built on top of our PBNJ library for the OSPRay renderer. It provides an easy to use API for showing fully interactive volume renderings to a web page.
eCamp: Visual Progression Analysis of Student Records Data
In this project we modeled and visualized progression in a complex societal system (a university campus), and told the story of choices with the insights from the data.
What would happen if you take the light source out from a scene and put it in the hands of the viewer (literally)? This was the main idea of my final project for the computer graphics course and here is a teaser gif of the results.
ThatOneLine: Annotating single lines of valuable code
ThatOneLine.com is a project for quickly annotating single lines of code for sharing and education.