Seminar by Siddhartha Chaudhuri
Content creation with semantic attributes
Siddhartha Chaudhuri
Princeton University
Date: Monday, October 21st, 2013
Time: 5:00 PM
Venue: CS101.Abstract:
Visual media surrounds us, and there is growing interest in new applications such as 3D printing and collaborative virtual worlds. As more and more people engage in producing visual content, there is a demand for interfaces that help novice users carry out creative design. Such an interface should allow people to easily and intuitively express high-level design goals, such as "create a fast airplane" or "create a cute toy", while allowing the final product to be customized according to each person's preferences.
Current interfaces require the design goal to be reached through careful planning and execution of a series of low-level drawing and editing commands -- which requires previsualization, dexterity and time -- or serendipitiously through largely unstructured exploration. The gap between how a person thinks about what she wants to create, and how she can interact with a computer to get there, is a barrier for the novice.
In this talk, I will present recent work on capturing design intent in high-level, linguistic terms. For example, the designer may want to make a virtual creature more "scary", or a web page more "artistic". Such requirements are natural for humans, yet cannot be directly expressed in current interfaces. Our work combines crowdsourcing, machine learning and probabilistic shape analysis to create a design interface that directly supports such expression. The approach is data-driven: large repositories of existing designs are used to learn shared structure and semantics, and repurposed for synthesizing new designs.
I will conclude with a discussion of directions, opportunities and challenges for new tools for high-level design that exploit the inter-relationship of semantics, function and form to aid the creative process.
About the speaker:
Siddhartha Chaudhuri is a postdoctoral researcher at Princeton University. He obtained his PhD from Stanford University in 2011, where he was supported by a Stanford Graduate Fellowship. His research focuses on richer tools for visual content creation, particularly for novice and casual users, and on problems in 3D reconstruction and synthesis. This research is driven by a more abstract interest in shape understanding at both the structural and semantic levels. In the past, he has also worked on theoretical computational geometry and very large-scale real-time rendering systems. His work has been published at the top computer graphics and human-computer interaction conferences, and is also the basis for a commercial 3D modeling system.