Proceedings of the IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017)

The matching points methods for solving the problem of the tracking objects

Authors
Polina Kovalenko, Andrey Mikhaylov, Alexander Kataev, Vladimir Rozaliev, Yulia Orlova
Corresponding Author
Polina Kovalenko
Available Online December 2017.
DOI
https://doi.org/10.2991/itsmssm-17.2017.47How to use a DOI?
Keywords
computer vision, detection, key point, descriptor, image, tracking.
Abstract

This article interprets a concept of key points and its descriptors, object tracking and key points matching goals. The concept of object detection and detection classification methods are described. Key points matching methods based on standard OpenCV functions and matching machine learning methods are described. Comparative analysis of these methods working is represented by following parameters: standard deviation, maximum axis deviation, average operating time and execution accuracy.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017)
Series
Advances in Computer Science Research
Publication Date
December 2017
ISBN
978-94-6252-432-3
ISSN
2352-538X
DOI
https://doi.org/10.2991/itsmssm-17.2017.47How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Polina Kovalenko
AU  - Andrey Mikhaylov
AU  - Alexander Kataev
AU  - Vladimir Rozaliev
AU  - Yulia Orlova
PY  - 2017/12
DA  - 2017/12
TI  - The matching points methods for solving the problem of the tracking objects
BT  - Proceedings of the IV International research conference "Information technologies in Science, Management, Social sphere and Medicine" (ITSMSSM 2017)
PB  - Atlantis Press
SP  - 223
EP  - 226
SN  - 2352-538X
UR  - https://doi.org/10.2991/itsmssm-17.2017.47
DO  - https://doi.org/10.2991/itsmssm-17.2017.47
ID  - Kovalenko2017/12
ER  -