Thesis Details
Rozpoznání vzorů v obraze pomocí klasifikátorů
An AdaBoost algorithm for construction of strong classifier from several weak hypotesis will be presented in this work. Theoretical background of the algorithm and the method of construction of strong classifiers will be explained. WaldBoost extension to the algorithm will be described. The thesis deals with image features that are often used as element of weak classifiers. Brief introduction to pattern recognition in context of computer vision will be outlined in the begining of the work. Also some widely used methods of classifier training will be presented. An object detection library based on AdaBoost classifiers was developed as part of the work. The library was used in implementation of software that in praktice demonstrates object detection in videosquences. Last part of the work describes tool for training of AdaBoost classifiers.
Pattern recognition, AdaBoost, WaldBoost, Classification, Detection, Image Features
Fučík Otto, doc. Dr. Ing. (DCSY FIT BUT), člen
Křena Bohuslav, Ing., Ph.D. (DITS FIT BUT), člen
Racek Stanislav, doc. Ing., CSc. (WBU in Pilsen), člen
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT), člen
Vojnar Tomáš, prof. Ing., Ph.D. (DITS FIT BUT), člen
@mastersthesis{FITMT2620,
author = "Roman Jur\'{a}nek",
type = "Master's thesis",
title = "Rozpozn\'{a}n\'{i} vzor\r{u} v obraze pomoc\'{i} klasifik\'{a}tor\r{u}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2007,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/2620/"
}