Year
2016
Degree Name
Doctor of Philosophy
Department
School of electrical, computer and telecommunications engineering
Recommended Citation
Nawaz, Muhammad Wasim, Sparse variational regularization for visual motion estimation, Doctor of Philosophy thesis, School of electrical, computer and telecommunications engineering, University of Wollongong, 2016. https://ro.uow.edu.au/theses/4641
Abstract
The computation of visual motion is a key component in numerous computer vision tasks such as object detection, visual object tracking and activity recognition. Despite exten- sive research effort, efficient handling of motion discontinuities, occlusions and illumina- tion changes still remains elusive in visual motion estimation. The work presented in this thesis utilizes variational methods to handle the aforementioned problems because these methods allow the integration of various mathematical concepts into a single en- ergy minimization framework. This thesis applies the concepts from signal sparsity to the variational regularization for visual motion estimation. The regularization is designed in such a way that it handles motion discontinuities and can detect object occlusions.
FoR codes (2008)
0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING
Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.