Publication Details

VTApi: an Efficient Framework for Computer Vision Data Management and Analytics

CHMELAŘ Petr, PEŠEK Martin, VOLF Tomáš, ZENDULKA Jaroslav and FRÖML Vojtěch. VTApi: an Efficient Framework for Computer Vision Data Management and Analytics. In: Advanced Concepts for Intelligent Vision Systems (ACIVS) - Proceedings of the 15th International Conference, ACIVS 2013. Lecture Notes in Computer Science (LNCS), Volume 8192 2013. Poznań: Springer London, 2013, pp. 378-388. ISBN 978-3-319-02894-1.
Czech title
VTApi: efektivní framework pro správu a analýzu dat počítačového vidění
Type
conference paper
Language
english
Authors
Chmelař Petr, Ing. (DIFS FIT BUT)
Pešek Martin, Ing. (DIFS FIT BUT)
Volf Tomáš, Ing. (DIFS FIT BUT)
Zendulka Jaroslav, doc. Ing., CSc. (DIFS FIT BUT)
Fröml Vojtěch, Ing. (FIT BUT)
Keywords

VTApi, computer vision, data management, similarity search, clustering, API, methodology, spatio-temporal

Abstract

VTApi is an open source application programming interface designed to fulfill the needs of specific distributed computer vision data and metadata management and analytic systems and to unify and accelerate their development. It is oriented towards processing and efficient management of image and video data and related metadata fortheir retrieval, analysis and mining with the special emphasis on their spatio-temporal nature in real-world conditions. VTApi is a free extensible framework based on progressive and scalable open source software as OpenCV for high- performance computer vision and data mining, PostgreSQL for efficient data management, indexing and retrieval extendedby similarity search and integrated with geography/spatio-temporal data manipulation.

Published
2013
Pages
378-388
Proceedings
Advanced Concepts for Intelligent Vision Systems (ACIVS) - Proceedings of the 15th International Conference, ACIVS 2013
Series
Lecture Notes in Computer Science (LNCS), Volume 8192 2013
Conference
Advanced Concepts for Intelligent Vision Systems, City Park Hotel, Poznan, PL
ISBN
978-3-319-02894-1
Publisher
Springer London
Place
Poznań, PL
DOI
10.1007/978-3-319-02895-8_34
BibTeX 
@INPROCEEDINGS{FITPUB10320,
   author = "Petr Chmela\v{r} and Martin Pe\v{s}ek and Tom\'{a}\v{s} Volf and Jaroslav Zendulka and Vojt\v{e}ch Fr{\"{o}}ml",
   title = "VTApi: an Efficient Framework for Computer Vision Data Management and Analytics",
   pages = "378--388",
   booktitle = "Advanced Concepts for Intelligent Vision Systems (ACIVS) - Proceedings of the 15th International Conference, ACIVS 2013",
   series = "Lecture Notes in Computer Science (LNCS), Volume 8192 2013",
   year = 2013,
   location = "Pozna\'{n}, PL",
   publisher = "Springer London",
   ISBN = "978-3-319-02894-1",
   doi = "10.1007/978-3-319-02895-8\_34",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/10320"
}
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