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Advances in Motion Estimators for Applications in Computer Vision

Abstract Motion estimation is a core task in computer vision and many applications utilize optical flow methods as fundamental tools to analyze motion in images and videos. Optical flow is the apparent motion of objects in image sequences that results from relative motion between the objects and the imaging perspective. Today, optical flow fields are utilized to solve problems in various areas such as object detection and tracking, interpolation, visual odometry, etc. In this dissertation, three problems from different areas of computer vision and the solutions that make use of modified optical flow methods are explained.

The contributions of this dissertation are approaches and frameworks that introduce i) a new optical flow-based interpolation me... (more)
Created Date 2018
Contributor Kanberoglu, Berkay (Author) / Frakes, David (Advisor) / Turaga, Pavan (Advisor) / Spanias, Andreas (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Biomedical engineering / Change detection / Interpolation / Motion estimation / Neuronavigation / Optical flow / Synthetic aperture radar
Type Doctoral Dissertation
Extent 152 pages
Language English
Note Doctoral Dissertation Electrical Engineering 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis