Now showing items 1-4 of 4
Physics-driven variational methods for computer vision and shape-based imaging
(Georgia Institute of Technology, 2014-05-13)
In this dissertation, novel variational optical-flow and active-contour methods are investigated to address challenging problems in computer vision and shape-based imaging. Starting from traditional applications of these ...
Statistical and geometric methods for visual tracking with occlusion handling and target reacquisition
(Georgia Institute of Technology, 2012-01-17)
Computer vision is the science that studies how machines understand scenes and automatically make decisions based on meaningful information extracted from an image or multi-dimensional data of the scene, like human vision. ...
Statistical and geometric methods for shape-driven segmentation and tracking
(Georgia Institute of Technology, 2008-03-05)
Computer Vision aims at developing techniques to extract and exploit information from images. The successful applications of computer vision approaches are multiple and have benefited diverse fields such as manufacturing, ...
Global Optimizing Flows for Active Contours
(Georgia Institute of Technology, 2007-07-09)
This thesis makes significant contributions to the object detection problem in computer vision. The object detection problem is, given a digital image of a scene, to detect the relevant object in the image. One technique ...