Selection-based dictionary learning for sparse representation invisual tracking
Published in Rutgers University Community Repository (Rutgers University) • Jan 1, 2012
Authors:
Casimir A. Kulikowski
Abstract
This dissertation describes a novel selection-based dictionary learning method with a sparse representation to tackle the object tracking problem in computer vision. The sparse representa- tion has been widely used in many applications including visual tracking, compressive sensing, image de-noising...
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