Title:
Constrained PDE optimization methods for motion segmentation and layer extraction

dc.contributor.advisor Yezzi, Anthony
dc.contributor.advisor Vela, Patricio A.
dc.contributor.author Jafri, Fareed Ud Din M.
dc.contributor.committeeMember AlRegib, Ghassan
dc.contributor.committeeMember Verriest, Erik
dc.contributor.committeeMember Kang, Sung Ha
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2019-01-16T17:22:46Z
dc.date.available 2019-01-16T17:22:46Z
dc.date.created 2018-12
dc.date.issued 2018-10-24
dc.date.submitted December 2018
dc.date.updated 2019-01-16T17:22:46Z
dc.description.abstract A layered representation of images allows us to capture motion, shape, appearance and occlusion structure without going into the complexity of a full 3D representation of the scene. A unified computational framework to integrate much of the current and prior work on layered models in the framework of PDEs and calculus of variations is presented. A novelty of this modeling technique is that it relaxes the \textit{brightness constancy constraint} for moving objects making the model a better fit for tracking objects in most real life scenarios. The technique links to the simplification of an earlier approach to layering (Jackson 2008) which significantly reduces the computational complexity of the model yet still provides enough modeling richness for pertinent applications. More importantly a subtle yet fundamental modeling flaw in this earlier work is discovered which severely degraded the performance of the technique. The cause of this is traced to a bias in the original formulation that improperly extended the classical Mumford-Shah segmentation model to layering which unintentionally penalized layer occlusion thereby producing the effect. The problem is resolved by replacing the prior joint shape and appearance optimization strategy with an alternative Lagrangian style constrained shape optimization subject to PDE based appearance constraints. MOVE (Moving Object Video Encoding), a novel technique for representing video that utilizes the framework is introduced.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/60748
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Layered models
dc.subject Active contours
dc.subject Mumford-Shah
dc.subject PDEs
dc.title Constrained PDE optimization methods for motion segmentation and layer extraction
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Yezzi, Anthony
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication 53ee63a2-04fd-454f-b094-02a4601962d8
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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