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

被引：0
|
作者：
Chmelar, Petr [1 ]
Pesek, Martin [1 ]
Volf, Tomas [1 ]
Zendulka, Jaroslav [1 ,2 ]
Froml, Vojtech [1 ]
机构：
[1] Brno Univ Technol, Fac Informat Technol, Bozetechova 1-2, Brno 61266, Czech Republic
[2] Brno Univ Technol, Ctr Excellence IT4Innovat, Brno 61266, Czech Republic
来源：
ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2013 | 2013年 / 8192卷
关键词：
VTApi; computer vision; data management; similarity search; clustering; API; methodology; spatio-temporal; MULTIMEDIA;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 for their 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 extended by similarity search and integrated with geography/spatio-temporal data manipulation.
引用
收藏
页码：378 / 388
页数：11
相关论文
共 50 条
  • [1] Possibilities of using computer vision for data analytics in medicine
    Iliashenko, O. Yu
    Lukyanchenko, E. L.
    IZVESTIYA OF SARATOV UNIVERSITY MATHEMATICS MECHANICS INFORMATICS, 2022, 22 (02): : 224 - 232
  • [2] A big data analytics framework for scientific data management
    Fiore, Sandro
    Palazzo, Cosimo
    D'Anca, Alessandro
    Foster, Ian
    Williams, Dean N.
    Aloisio, Giovanni
    2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2013,
  • [3] Editorial "Computer Vision and Big Data Analytics for Remote Sensing"
    Sagan, Vasit
    Paheding, Sidike
    Wang, Dongodng
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2018, 84 (07): : 423 - 423
  • [4] Framework of Data Analytics and Integrating Knowledge Management
    Schaefer C.
    Makatsaria A.
    International Journal of Intelligent Networks, 2021, 2 : 156 - 165
  • [5] A Hybrid Efficient Data Analytics Framework for Stroke Prediction
    Alhakami, Hosam
    Alraddadi, Shouq
    Alseady, Shurug
    Baz, Abdullah
    Alsubait, Tahani
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2020, 20 (04): : 240 - 250
  • [6] An image processing and computer vision framework for efficient robotic sketching
    Tiwari, Mayank
    Lamba, Subir Singh
    Gupta, Bhupendra
    INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018), 2018, 133 : 284 - 289
  • [7] Big Data Analytics Framework for Natural Disaster Management in Malaysia
    Abdullah, Mohammad Fikry
    Ibrahim, Mardhiah
    Zulkifli, Harlisa
    IOTBDS: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, BIG DATA AND SECURITY, 2017, : 406 - 411
  • [8] A Computer Cluster for Big Data and Data Analytics Management: Design, Implementation, and Assessment
    Garcia-Ojeda, J. C.
    Luna Ortiz, Meleny
    Sanchez Garcia, Rodolfo
    Hernandez Caceres, Javier
    Argoti, Andres
    PROCEEDINGS OF THE EURO AMERICAN CONFERENCE ON TELEMATICS AND INFORMATION SYSTEMS (EATIS '18), 2018,
  • [9] BigFuzz: Efficient Fuzz Testing for Data Analytics Using Framework Abstraction
    Zhang, Qian
    Wang, Jiyuan
    Gulzar, Muhammad Ali
    Padhye, Rohan
    Kim, Miryung
    2020 35TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING (ASE 2020), 2020, : 722 - 733
  • [10] Amateur football analytics using computer vision
    Mavrogiannis, Panagiotis
    Maglogiannis, Ilias
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (22): : 19639 - 19654
12345