Thesis Details

HUMAN ACTION RECOGNITION IN VIDEO

Ph.D. Thesis Student: Řezníček Ivo Academic Year: 2014/2015 Supervisor: Zemčík Pavel, prof. Dr. Ing.
Czech title
ROZPOZNÁNÍ ČINNOSTÍ ČLOVĚKA VE VIDEU
Language
English
Abstract

This thesis focuses on the improvement of human action recognition systems. It reviews the state-of-the-art in the field of action recognition from video. It describes techniques of digital image and video capture, and explains computer representations of image and video. This thesis further describes how local feature vectors and local space-time feature vectorsare used, and how captured data is prepared for further analysis, such as classification methods. This is typically done with video segments of arbitrarily varying length. The key contribution of this work explores the hypothesis that the analysis of different types of actions requires different segment lenghts to achieve optimal quality of recognition. An algorithm to find these optimal lengths is proposed, implemented, and tested. Using this algorithm, the hypothesis was experimentally proven. It was also shown that by finding the optimal length, the prediction and classification power of current algorithms is improved upon. Supporting experiments, results, and proposed exploitations of these findings are presented.

Keywords

Optimal analysis length of action, local space-time features, bag-of-words repesentation, visual vocabulary, SVM.

Department
Degree Programme
Information Technology, Field of Study Information Technology
Files
Status
defended
Date
19 December 2014
Citation
ŘEZNÍČEK, Ivo. HUMAN ACTION RECOGNITION IN VIDEO. Brno, 2014. Ph.D. Thesis. Brno University of Technology, Faculty of Information Technology. 2014-12-19. Supervised by Zemčík Pavel. Available from: https://www.fit.vut.cz/study/phd-thesis/306/
BibTeX
@phdthesis{FITPT306,
    author = "Ivo \v{R}ezn\'{i}\v{c}ek",
    type = "Ph.D. thesis",
    title = "HUMAN ACTION RECOGNITION IN VIDEO",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2014,
    location = "Brno, CZ",
    language = "english",
    url = "https://www.fit.vut.cz/study/phd-thesis/306/"
}
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