Thesis Details
Detekce obličeje v nekvalitních videozáznamech
This bachelor thesis deals with face detection in low quality videos, while mainly focusing on occluded faces. It describes elementary priciples of machine learning algorithms and their methods, which are often used in the field of computer vision. Out of them are more closely described convolutional neural networks and their state of the art models focused on face detection. Out of those, convolutional neural networks and state of the art models for face detection are more closely described. For the practical part face detection models inspired by state of the art model RetinaFace were implemented and trained. The best performing model achieves 85.5% average precision on WIDER Face HARD testing dataset and 90.9% on dataset focused on occluded faces. Part of this thesis is also a program with graphical user interfaces which provides tools to use developed models on videos and pictures.
face detection, closed circuit cameras, poor quality videos, neural networks, machine learning, convolutional neural networks, Keras, RetinaFace, WIDER Face, occluded faces
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Grégr Matěj, Ing., Ph.D. (DIFS FIT BUT), člen
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
@bachelorsthesis{FITBT22953,
author = "Michal Koval",
type = "Bachelor's thesis",
title = "Detekce obli\v{c}eje v nekvalitn\'{i}ch videoz\'{a}znamech",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "slovak",
url = "https://www.fit.vut.cz/study/thesis/22953/"
}