Publication result detail

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

CHMELAŘ, P.; PEŠEK, M.; VOLF, T.; ZENDULKA, J.; FRÖML, V.

Original Title

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

English Title

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

Type

Paper in proceedings outside WoS and Scopus

Original 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.

English 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.

Keywords

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

Key words in English

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

Authors

CHMELAŘ, P.; PEŠEK, M.; VOLF, T.; ZENDULKA, J.; FRÖML, V.

RIV year

2014

Released

26.09.2013

Publisher

Springer London

Location

Poznań

ISBN

978-3-319-02894-1

Book

Advanced Concepts for Intelligent Vision Systems (ACIVS) - Proceedings of the 15th International Conference, ACIVS 2013

Edition

Lecture Notes in Computer Science (LNCS), Volume 8192 2013

Pages from

378

Pages to

388

Pages count

11

URL

https://www.fit.vut.cz/research/publication/10320/

BibTex

@inproceedings{BUT103486,
  author="Petr {Chmelař} and Martin {Pešek} and Tomáš {Volf} and Jaroslav {Zendulka} and Vojtěch {Fröml}",
  title="VTApi: an Efficient Framework for Computer Vision Data Management and Analytics",
  booktitle="Advanced Concepts for Intelligent Vision Systems (ACIVS) - Proceedings of the 15th International Conference, ACIVS 2013",
  year="2013",
  series="Lecture Notes in Computer Science (LNCS), Volume 8192 2013",
  pages="378--388",
  publisher="Springer London",
  address="Poznań",
  doi="10.1007/978-3-319-02895-8\{_}34",
  isbn="978-3-319-02894-1",
  url="https://www.fit.vut.cz/research/publication/10320/"
}

Documents

mdmm_vtapi
acivs2013_vtapi