Advances in RGB and RGBD Generic Object Trackers

Handle URI:
http://hdl.handle.net/10754/609455
Title:
Advances in RGB and RGBD Generic Object Trackers
Authors:
Bibi, Adel ( 0000-0002-6169-3918 )
Abstract:
Visual object tracking is a classical and very popular problem in computer vision with a plethora of applications such as vehicle navigation, human computer interface, human motion analysis, surveillance, auto-control systems and many more. Given the initial state of a target in the first frame, the goal of tracking is to predict states of the target over time where the states describe a bounding box covering the target. Despite numerous object tracking methods that have been proposed in recent years [1-4], most of these trackers suffer a degradation in performance mainly because of several challenges that include illumination changes, motion blur, complex motion, out of plane rotation, and partial or full occlusion, while occlusion is usually the most contributing factor in degrading the majority of trackers, if not all of them. This thesis is devoted to the advancement of generic object trackers tackling different challenges through different proposed methods. The work presented propose four new state-of-the-art trackers. One of which is 3D based tracker in a particle filter framework where both synchronization and registration of RGB and depth streams are adjusted automatically, and three works in correlation filters that achieve state-of-the-art performance in terms of accuracy while maintaining reasonable speeds.
Advisors:
Ghanem, Bernard ( 0000-0002-5534-587X )
Committee Member:
Al-Naffouri, Tareq Y.; Heidrich, Wolfgang ( 0000-0002-4227-8508 )
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program
Program:
Electrical Engineering
Issue Date:
Apr-2016
Type:
Thesis
Appears in Collections:
Theses; Electrical Engineering Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorGhanem, Bernarden
dc.contributor.authorBibi, Adelen
dc.date.accessioned2016-05-15T11:49:21Zen
dc.date.available2016-05-15T11:49:21Zen
dc.date.issued2016-04en
dc.identifier.urihttp://hdl.handle.net/10754/609455en
dc.description.abstractVisual object tracking is a classical and very popular problem in computer vision with a plethora of applications such as vehicle navigation, human computer interface, human motion analysis, surveillance, auto-control systems and many more. Given the initial state of a target in the first frame, the goal of tracking is to predict states of the target over time where the states describe a bounding box covering the target. Despite numerous object tracking methods that have been proposed in recent years [1-4], most of these trackers suffer a degradation in performance mainly because of several challenges that include illumination changes, motion blur, complex motion, out of plane rotation, and partial or full occlusion, while occlusion is usually the most contributing factor in degrading the majority of trackers, if not all of them. This thesis is devoted to the advancement of generic object trackers tackling different challenges through different proposed methods. The work presented propose four new state-of-the-art trackers. One of which is 3D based tracker in a particle filter framework where both synchronization and registration of RGB and depth streams are adjusted automatically, and three works in correlation filters that achieve state-of-the-art performance in terms of accuracy while maintaining reasonable speeds.en
dc.language.isoenen
dc.subjectTrackersen
dc.subjectCorrelation Filtersen
dc.subjectConvolution Filtersen
dc.subjectSparse representationen
dc.subjectRGBD Trackersen
dc.subjectSynchronizationen
dc.subjectRegistrationen
dc.titleAdvances in RGB and RGBD Generic Object Trackersen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberAl-Naffouri, Tareq Y.en
dc.contributor.committeememberHeidrich, Wolfgangen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.nameMaster of Scienceen
dc.person.id134121en
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