INCREMENTAL LEARNING OF EVENTS IN VIDEO USING RELIABLE INFORMATION

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INCREMENTAL LEARNING OF EVENTS IN VIDEO USING RELIABLE INFORMATION

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DESCARGA ADJUNTOS
Autor: ZUÑIGA, MARCOS
Académico Guía: THONNAT, MONIQUE
Grado: DOCTOR EN CIENCIAS ESPECIALIDAD INFORMATICA
Tipo de Recurso: Tesis Doctorado
Fecha de publicación: 2008
Idioma: eng
País: FRANCIA
Disciplina Fondecyt: INFORMATICA
Resumen: The goal of this thesis is to propose a general video understanding framework for learning and recognition of events occurring in videos, for real world applications. This video understanding framework is composed of four tasks: First, at each video frame, a segmentation task detects the moving regions, represented by bounding boxes enclosing them. Second, a new 3D classifier associates to each moving region an object class label (e.g. person, vehicle) and a 3D parallelepiped described by its

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