Research Interests
- Computer Vision
- Video Image Processing
- Human-Computer Interaction
- Machine Learning in Vision
- Information Hiding
Demos and presentations
Current Research
The central theme of my computer vision research is understanding the
motions of humans and of vehicles driven by humans. Application
areas for this research include smart rooms, video surveillance
and monitoring, human-computer interaction, secure driving/
intelligent highways, and video coding.
In my work I have been applying techniques from such domains as
theoretical kinematics and dance notation to analyze physical and
geometrical constraints on the motions of humans and vehicles. This research
will result in methods that significantly improve on currently available
techniques for computing human-generated motions of objects. In my
previous work I have developed the Frenet-Serret and Darboux motion models to
describe physically possible motions of tools and vehicles. In my current
work I am extending this research to understanding human motions. In
particular I am investigating how dance notation can be used to describe
human motions in such domains as gestures and sports.
In the domain of human motion understanding I am interested in gestures
and simple activities performed by small numbers of humans. In the
gesture domain a single human is viewed by one or more cameras. The
human uses upper body gestures such as posture, head pose (nods, etc.),
shoulder movements (shrugs, etc.), hand and arm movements, palm facings,
finger pointings, and so on to convey a message. In the domain of
``general'' human motions and sports we are interested in simple movements
that are performed in an approximately upright position, such as walking,
running, etc.
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Department of Computer Science
George Mason University
Last updated 10/25/2001.