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dc.contributorSanfeliu Cortés, Alberto
dc.contributor.authorVaquero Gómez, Víctor
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.description.abstractThis Master's Thesis presents a new developed algorithm that merges Appearance and Depth Images in order to perform the detection of objects in scenes. This new algorithm uses the approach of the Online Learning Random Ferns, proposed by Villamizar et al at [1]. Although Villamizar's detector takes only into account appearance information (RGB), the new developed algorithm will also use depth images for creating a robust Object Detector. In this way, it has been studied the best method for combining both sources of information in the same algorithm (appearance and depth). Several approaches to solve this, have been created and tested through a set of experiments, studying its effects over different scenarios and parameters configuration.
dc.publisherUniversitat Politècnica de Catalunya
dc.subjectÀrees temàtiques de la UPC::Informàtica::Robòtica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
dc.subject.lcshComputer vision
dc.subject.lcshPattern recognition systems
dc.subject.lcshImage converters
dc.subject.lcshMachine learning
dc.titleCombining depth with appearance images for object detection using online learning
dc.typeMaster thesis
dc.subject.lemacVisió per ordinador
dc.subject.lemacReconeixement de formes (Informàtica)
dc.subject.lemacImatges -- Convertidors
dc.subject.lemacAprenentatge automàtic
dc.rights.accessRestricted access - author's decision
dc.audience.mediatorEscola Tècnica Superior d'Enginyeria Industrial de Barcelona

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