Thesis Details

Identifikace chodců

Bachelor's Thesis Student: Jurča Jan Academic Year: 2018/2019 Supervisor: Hradiš Michal, Ing., Ph.D.
English title
Pedestrian Identification
Language
Czech
Abstract

This thesis deals with pedestrian identification from video sequence based on person, face and gait recognition. For person and face recognition are used pretrained networks. While for gait recognition is implemented and compared many different networks. Final pedestrian recognition is based on multimodal fusion realized by neural network. For the purpose of the work was created dataset, along with a set of tools that allow its almost automatic creation.

Keywords

Face recognition, person recognition, gait recognition, multimodal fusion, deep neural networks, dataset, convolutional neural networks, recurrent neural networks, siamese network, feature vector extraction, BUT Pedestrians

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
11 June 2019
Reviewer
Špaňhel Jakub, Ing.
Committee
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
Rogalewicz Adam, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Citation
JURČA, Jan. Identifikace chodců. Brno, 2019. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-11. Supervised by Hradiš Michal. Available from: https://www.fit.vut.cz/study/thesis/21088/
BibTeX 
@bachelorsthesis{FITBT21088,
    author = "Jan Jur\v{c}a",
    type = "Bachelor's thesis",
    title = "Identifikace chodc\r{u}",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/21088/"
}

Theses

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