{"id":{"repo_id":"missouri","oai_identifier":"oai:mospace.umsystem.edu:10355/11163"},"canonical_url":"https://search.dev.ndltd.org/etd/missouri/oai:mospace.umsystem.edu:10355/11163","repository":{"repo_id":"missouri","name":"University of Missouri","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Planar detection using modified expectation maximization","abstract":"In this work the task of planar detection in an image pair is cast as an incomplete data problem where the parameters to be estimated are the ones that define the homographies induced by the planar regions in the scene. This incomplete data problem motivates the employment of the Expectation Maximization (EM) algorithm. Derivation of the EM algorithm equations proves that a closed form solution to the maximization step is impractical which leads to the proposal of a Modified Expectation Maximization (MEM) algorithm. The MEM algorithm presented replaces the traditional maximization step with an optimization based maximization step or a Kalman Filter based maximization step. In addition to this, recommendations are provided to reduce the number of parameters that need to be estimated by the MEM algorithm depending on the constraints of the scene. Experimental results show that the proposed MEM algorithm achieves comparable results to current methods for planar detection.","abstract_html":"In this work the task of planar detection in an image pair is cast as an incomplete data problem where the parameters to be estimated are the ones that define the homographies induced by the planar regions in the scene. This incomplete data problem motivates the employment of the Expectation Maximization (EM) algorithm. Derivation of the EM algorithm equations proves that a closed form solution to the maximization step is impractical which leads to the proposal of a Modified Expectation Maximization (MEM) algorithm. The MEM algorithm presented replaces the traditional maximization step with an optimization based maximization step or a Kalman Filter based maximization step. In addition to this, recommendations are provided to reduce the number of parameters that need to be estimated by the MEM algorithm depending on the constraints of the scene. Experimental results show that the proposed MEM algorithm achieves comparable results to current methods for planar detection.","abstract_has_math":false,"creators":["Conrad, Daniel, 1986-"],"institution":"University of Missouri--Columbia","degree_name":"M.S.","degree_level":"Masters","degree_discipline":"Electrical and computer engineering (MU)","degree_department":null,"school":null,"contributors":[],"advisors":["DeSouza, Guilherme"],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-24T03:07:13Z","subjects":[],"languages":["eng","English"],"rights":["OpenAccess."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10355/11163","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["DeSouza, Guilherme"]},{"key":"dc:creator","label":"Author","values":["Conrad, Daniel, 1986-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2011-07-20T13:56:25Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2011-07-20T13:56:25Z"]},{"key":"dc:date.issued","label":"Date","values":["2011"]},{"key":"dc:publisher","label":"Institution","values":["University of Missouri--Columbia"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and computer engineering (MU)"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Columbia"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["OpenAccess."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10355/11163"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Title from PDF of title page (University of Missouri--Columbia, viewed on May 26, 2011).","The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.","Thesis advisor: Dr. Guilherme DeSouza.","Includes bibliographical references.","M.S. University of Missouri--Columbia 2011."]},{"key":"dc:description.abstract","label":"Abstract","values":["In this work the task of planar detection in an image pair is cast as an incomplete data problem where the parameters to be estimated are the ones that define the homographies induced by the planar regions in the scene. This incomplete data problem motivates the employment of the Expectation Maximization (EM) algorithm. Derivation of the EM algorithm equations proves that a closed form solution to the maximization step is impractical which leads to the proposal of a Modified Expectation Maximization (MEM) algorithm. The MEM algorithm presented replaces the traditional maximization step with an optimization based maximization step or a Kalman Filter based maximization step. In addition to this, recommendations are provided to reduce the number of parameters that need to be estimated by the MEM algorithm depending on the constraints of the scene. Experimental results show that the proposed MEM algorithm achieves comparable results to current methods for planar detection."]},{"key":"dc:title","label":"Title","values":["Planar detection using modified expectation maximization"]}]}],"canonical_facts":{"dc:contributor.advisor":["DeSouza, Guilherme"],"dc:creator":["Conrad, Daniel, 1986-"],"dc:date.accessioned":["2011-07-20T13:56:25Z"],"dc:date.available":["2011-07-20T13:56:25Z"],"dc:date.issued":["2011"],"dc:description":["Title from PDF of title page (University of Missouri--Columbia, viewed on May 26, 2011).","The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.","Thesis advisor: Dr. Guilherme DeSouza.","Includes bibliographical references.","M.S. University of Missouri--Columbia 2011."],"dc:description.abstract":["In this work the task of planar detection in an image pair is cast as an incomplete data problem where the parameters to be estimated are the ones that define the homographies induced by the planar regions in the scene. This incomplete data problem motivates the employment of the Expectation Maximization (EM) algorithm. Derivation of the EM algorithm equations proves that a closed form solution to the maximization step is impractical which leads to the proposal of a Modified Expectation Maximization (MEM) algorithm. The MEM algorithm presented replaces the traditional maximization step with an optimization based maximization step or a Kalman Filter based maximization step. In addition to this, recommendations are provided to reduce the number of parameters that need to be estimated by the MEM algorithm depending on the constraints of the scene. Experimental results show that the proposed MEM algorithm achieves comparable results to current methods for planar detection."],"dc:identifier.uri":["http://hdl.handle.net/10355/11163"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["University of Missouri--Columbia"],"dc:rights":["OpenAccess."],"dc:title":["Planar detection using modified expectation maximization"],"dc:type":["Thesis"],"thesis:degree_discipline":["Electrical and computer engineering (MU)"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Missouri--Columbia"]},"updated_at":"2026-07-24T03:07:13Z"}