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Robustní metody a regrese
dc.creatorKalina, Jan
dc.date.accessioned2021-05-19T16:20:10Z
dc.date.available2021-05-19T16:20:10Z
dc.date.issued2008
dc.identifier.urihttp://hdl.handle.net/20.500.11956/14314
dc.description.abstractThis thesis is devoted to automatic location of landmarks (month and eyes) in images of faces using templates. There is an unsatisfactory experience with existing software because of its high sensitivity to small rotations of the face. The weighted correlation coefficient as a similarity measure between the template and the image turns out toout- perform the classical correlation. It is presented how to choose the weights to increase the discrimination of the parts of the face which correspond to the template from those which do not. Optimization without constraints tends to degenerate and to obtain a ro- bust version we bound the influence of single pixels. In a similar way the template can be optimized to improve the discrimination further. The results arc? compared for different initial choices of weights and their robustness to different size or rotation of the face is examined. The method docs not use any special properties of faces and can be classified as a robust nonparametric disrimination technique. Abstrakt Pra.ce HC zabyva, automatickym liledam'm objcktn (list a oci) v obrazech oblicejri za po- rnoci sabloii. Dostupny software je velmi citlivy k malym otocenim oblieje a zkusenost s mm je neuspokojiva. Vaznny korelarm koefieieiit je vhodnejsi mi'ron podobnosti mezi sablonou a obrazem nez...en_US
dc.description.abstractThis thesis is devoted to automatic location of landmarks (month and eyes) in images of faces using templates. There is an unsatisfactory experience with existing software because of its high sensitivity to small rotations of the face. The weighted correlation coefficient as a similarity measure between the template and the image turns out toout- perform the classical correlation. It is presented how to choose the weights to increase the discrimination of the parts of the face which correspond to the template from those which do not. Optimization without constraints tends to degenerate and to obtain a ro- bust version we bound the influence of single pixels. In a similar way the template can be optimized to improve the discrimination further. The results arc? compared for different initial choices of weights and their robustness to different size or rotation of the face is examined. The method docs not use any special properties of faces and can be classified as a robust nonparametric disrimination technique. Abstrakt Pra.ce HC zabyva, automatickym liledam'm objcktn (list a oci) v obrazech oblicejri za po- rnoci sabloii. Dostupny software je velmi citlivy k malym otocenim oblieje a zkusenost s mm je neuspokojiva. Vaznny korelarm koefieieiit je vhodnejsi mi'ron podobnosti mezi sablonou a obrazem nez...cs_CZ
dc.languageEnglishcs_CZ
dc.language.isoen_US
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.titleLocating Landmarks Using Templatesen_US
dc.typerigorózní prácecs_CZ
dcterms.created2008
dcterms.dateAccepted2008-02-25
dc.description.departmentDepartment of Probability and Mathematical Statisticsen_US
dc.description.departmentKatedra pravděpodobnosti a matematické statistikycs_CZ
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.identifier.repId57186
dc.title.translatedRobustní metody a regresecs_CZ
dc.identifier.aleph000965193
thesis.degree.nameRNDr.
thesis.degree.levelrigorózní řízenícs_CZ
thesis.degree.disciplineProbability, mathematical statistics and econometricsen_US
thesis.degree.disciplinePravděpodobnost, matematická statistika a ekonometriecs_CZ
thesis.degree.programMathematicsen_US
thesis.degree.programMatematikacs_CZ
uk.thesis.typerigorózní prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Katedra pravděpodobnosti a matematické statistikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Department of Probability and Mathematical Statisticsen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csPravděpodobnost, matematická statistika a ekonometriecs_CZ
uk.degree-discipline.enProbability, mathematical statistics and econometricsen_US
uk.degree-program.csMatematikacs_CZ
uk.degree-program.enMathematicsen_US
thesis.grade.csUznánocs_CZ
thesis.grade.enRecognizeden_US
uk.abstract.csThis thesis is devoted to automatic location of landmarks (month and eyes) in images of faces using templates. There is an unsatisfactory experience with existing software because of its high sensitivity to small rotations of the face. The weighted correlation coefficient as a similarity measure between the template and the image turns out toout- perform the classical correlation. It is presented how to choose the weights to increase the discrimination of the parts of the face which correspond to the template from those which do not. Optimization without constraints tends to degenerate and to obtain a ro- bust version we bound the influence of single pixels. In a similar way the template can be optimized to improve the discrimination further. The results arc? compared for different initial choices of weights and their robustness to different size or rotation of the face is examined. The method docs not use any special properties of faces and can be classified as a robust nonparametric disrimination technique. Abstrakt Pra.ce HC zabyva, automatickym liledam'm objcktn (list a oci) v obrazech oblicejri za po- rnoci sabloii. Dostupny software je velmi citlivy k malym otocenim oblieje a zkusenost s mm je neuspokojiva. Vaznny korelarm koefieieiit je vhodnejsi mi'ron podobnosti mezi sablonou a obrazem nez...cs_CZ
uk.abstract.enThis thesis is devoted to automatic location of landmarks (month and eyes) in images of faces using templates. There is an unsatisfactory experience with existing software because of its high sensitivity to small rotations of the face. The weighted correlation coefficient as a similarity measure between the template and the image turns out toout- perform the classical correlation. It is presented how to choose the weights to increase the discrimination of the parts of the face which correspond to the template from those which do not. Optimization without constraints tends to degenerate and to obtain a ro- bust version we bound the influence of single pixels. In a similar way the template can be optimized to improve the discrimination further. The results arc? compared for different initial choices of weights and their robustness to different size or rotation of the face is examined. The method docs not use any special properties of faces and can be classified as a robust nonparametric disrimination technique. Abstrakt Pra.ce HC zabyva, automatickym liledam'm objcktn (list a oci) v obrazech oblicejri za po- rnoci sabloii. Dostupny software je velmi citlivy k malym otocenim oblieje a zkusenost s mm je neuspokojiva. Vaznny korelarm koefieieiit je vhodnejsi mi'ron podobnosti mezi sablonou a obrazem nez...en_US
uk.file-availabilityV
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistikycs_CZ
thesis.grade.codeU
uk.publication-placePrahacs_CZ
uk.thesis.defenceStatusU


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