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H. Quynh Dinh: Grants
|Detecting Patterns in Vector Fields
Honda Initiation Grant, Honda Research Institute, 2009-2010.
Detecting patterns in vector fields will become increasingly crucial as computational methods for simulating fluid dynamics (CFD), sensor technology for dynamic data, and video surveillance increase in accuracy and ubiquity. The goal of this research is an in-depth study into how patterns can be detected in vector fields, starting with 2D fields and extending to fields over surfaces and in volumes (3D fields). Over the next 5 years, we will extend these algorithms to complex domains on simulated and recorded data via collaborations with researchers in automotive and ocean engineering and medical imaging.
|A Transderivational Search Engine for
Creative Analogy Generation in Mixed-Media Design
H.Q. Dinh and E. Fisher
National Science Foundation Creative IT Program, Award# IIS-0742440, 2007-2009.
Text-based search engines are now reaching maturity. More recently, content-based (non-textual) retrieval algorithms have been developed for music, images, video, and 3D shapes. The goal of this project is to develop a transderivational search engine that suggests analogies across different media forms (e.g., text, audio, images, video, and 3D shapes) by looking at structural similarity within media content. The search engine will be developed in the context of designing interactive, mixed-media installations and in a brainstorming application for artists and designers. The result will be a transformative technology at the intersection of art, computer graphics, machine learning, cognitive psychology, and human-computer interaction (HCI). Project Webpage
|Automated Construction of Digital Models from Real Artifacts
H.Q. Dinh, G. Turk, G. Slabaugh, and R. Schafer
GVU Seed Grant, 2000
Quality graphics is a growing presence in the home due to the diminishing price of computer hardware. As computers become more prevalent, activities such as creating web pages, image editing, and video editing have become more commonplace and no longer require professional training. Creating digital models, however, require special equipment or training. The goal of this project is to develop automated methods that will enable non-professional, home PC users, and graphic art enthusiasts to create their own digital models from existing artifacts.