{"id":21655,"date":"2018-03-09T09:11:31","date_gmt":"2018-03-09T09:11:31","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/uso-del-flujo-optico-en-algoritmos-probabila%c2%adsticos-de-seguimiento\/"},"modified":"2018-03-09T09:11:31","modified_gmt":"2018-03-09T09:11:31","slug":"uso-del-flujo-optico-en-algoritmos-probabila%c2%adsticos-de-seguimiento","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/uso-del-flujo-optico-en-algoritmos-probabila%c2%adsticos-de-seguimiento\/","title":{"rendered":"Uso del flujo \u00f3ptico en algoritmos probabil\u00edsticos de seguimiento"},"content":{"rendered":"<h2>Tesis doctoral de <strong>  Lucena L\u00f3pez Manuel Jos\u00e9 <\/strong><\/h2>\n<p>El flujo \u00f3ptico constituye una caracter\u00edstica de gran inter\u00e9s en procesamiento de im\u00e1genes. De hecho, disponiendo de una estimaci\u00f3n totalmente precisa y completa el flujo en todos los cuadros de una secuencia y conociendo las posiciones de los objetos que la integran, podr\u00edan ser empleado de forma directa para llevar a cabo tareas de seguimiento. Sin embargo, el c\u00e1lculo del flujo presenta serias dificultades, debido, entre otras cosas, al gran n\u00famero de fen\u00f3menos que intervienen en la formaci\u00f3n de las im\u00e1genes en el sensor y a que las hip\u00f3tesis que se utilizan suelen resultar insuficientes para caracterizarlo completamente. No obstante, existen m\u00faltiples algoritmos capaces de proporcionar estimaciones razonables de flujo, y adem\u00e1s indicar en qu\u00e9 puntos de la imagen dichas estimaciones son m\u00e1s fiables.  los algoritmos probabil\u00edsticos han demostrado una gran adecuaci\u00f3n a las tareas de seguimiento, ya que manejan de forma natural informaci\u00f3n incompleta o imprecisa. M\u00e1s concretamente, los algoritmos de filtrado de part\u00edculas, com condensation, que representan las distribuciones de probabilidad involucradas en el proceso mediante conjuntos aleatorios de muestras, permiten trabajar en situaciones en las que dichas distribuciones no son gaussianas.  en esta tesis se analiza el rendimiento de diferentes algoritmos de c\u00e1lculo de flujo \u00f3ptico en situaciones t\u00edpicas de seguimiento, empleando varias medidas que permiten cuantificar los errores cometidos en el proceso de estimaci\u00f3n del fujo. Tambi\u00e9n se define una serie de mdoelos de observaci\u00f3n basados en flujo \u00f3ptico, v\u00e1lidos para ser empleados a la hora de hacer seguimiento mediante algoritmos de filtrado de part\u00edculas.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Uso del flujo \u00f3ptico en algoritmos probabil\u00edsticos de seguimiento<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Uso del flujo \u00f3ptico en algoritmos probabil\u00edsticos de seguimiento <\/li>\n<li><strong>Autor:<\/strong>\u00a0  Lucena L\u00f3pez Manuel Jos\u00e9 <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Granada<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 17\/02\/2003<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Nicolas Perez De La Blanca Capilla<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: rafael Molina soriano <\/li>\n<li>nicolas Guil matas (vocal)<\/li>\n<li>filiberto Pla ba\u00f1\u00f3n (vocal)<\/li>\n<li> Fuertes Garc\u00eda Jos\u00e9 Manuel (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Lucena L\u00f3pez Manuel Jos\u00e9 El flujo \u00f3ptico constituye una caracter\u00edstica de gran inter\u00e9s en procesamiento de im\u00e1genes. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[2207,1890,1477,2528,126],"tags":[11903,65195,65194,55716,3618,35557],"class_list":["post-21655","post","type-post","status-publish","format-standard","hentry","category-analisis-de-datos","category-ciencia-de-los-ordenadores","category-estadistica","category-inteligencia-artificial","category-matematicas","tag-filiberto-pla-banon","tag-fuertes-garcia-jose-manuel","tag-lucena-lopez-manuel-jose","tag-nicolas-guil-matas","tag-nicolas-perez-de-la-blanca-capilla","tag-rafael-molina-soriano"],"_links":{"self":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/21655","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/comments?post=21655"}],"version-history":[{"count":0,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/21655\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/media?parent=21655"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/categories?post=21655"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/tags?post=21655"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}