Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/3330393.3330420acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicmsspConference Proceedingsconference-collections
research-article

Assessment of the effectiveness and sustainability of the detection of diverse features in an unknown background environment of the real scene

Published: 10 May 2019 Publication History

Abstract

Research is focused on the effect of changes in the observation conditions on the effectiveness of the detection of diverse features on real scene with illumination variance, it is revealed that the use of a proposed robust detector allows ensuring stable repeatability of results of detection of features in comparison with existing detectors of image features

References

[1]
E. N. Mortensen, H. Deng, and L. Shapiro, "A SIFT descriptor with global context," Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., vol. 1, pp. 184--190, 2005.
[2]
A. Leonardis, H. Bischof, A. Pinz, H. Bay, T. Tuytelaars, and L. Van Gool, Computer Vision -- ECCV 2006 SURF: Speeded Up Robust Features, vol. 3951. 2006.
[3]
W. Maddern, A. D. Stewart, C. McManus, B. Upcroft, W. Churchill, and P. Newman, "Illumination Invariant Imaging: Applications in Robust Vision-based Localisation, Mapping and Classification for Autonomous Vehicles," Proc. Vis. Place Recognit. Chang. Environ. Work. IEEE Int. Conf. Robot. Autom., 2014.
[4]
D. Petrov and K. Rumyantsev, "Analysis of the Effectiveness of the Robust Contrast Feature Detector," in 2017 2nd International Conference on Multimedia and Image Processing (ICMIP), 2017, pp. 43--47.
[5]
K. Rumyantsev and D. Petrov, "Universal robust algorithm for detection of image features," in Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2016, vol. 2016-Sep., pp. 3061--3065.
[6]
K. Rumyantsev and D. Petrov, "An analysis of feature detection efficiency on images with a priori unknown and changing viewing conditions," in 5th International Conference on Informatics, Electronics & Vision (ICIEV), 2016, pp. 570--573.
[7]
J. a Rice, Mathematical Statistics and Data Analysis, vol. 72, no. 462. 1995.
[8]
K. E. Rumyantsev and D.A. Petrov, "UNIVERSAL ROBUST ALGORITHM FOR DETECTION OF FEATURES ON A SCENE," Izv. SFEDU. Eng. Sci., vol. 8, no. 170, pp. 119--137, 2015.
[9]
K. E. Rumyantsev and D.A. Petrov, "Informativity of natural halftone landscapes," Fundam. Res., vol. 5, pp. 329--334, 2015.
[10]
V. Vonikakis, D. Chrysostomou, R. Kouskouridas, and A. Gasteratos, "Improving the robustness in feature detection by local contrast enhancement," in IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings, 2012.

Index Terms

  1. Assessment of the effectiveness and sustainability of the detection of diverse features in an unknown background environment of the real scene

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICMSSP '19: Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing
    May 2019
    213 pages
    ISBN:9781450371711
    DOI:10.1145/3330393
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Shenzhen University: Shenzhen University
    • Sun Yat-Sen University

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 10 May 2019

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. feature detector
    2. image features
    3. image processing
    4. robust detector

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Funding Sources

    Conference

    ICMSSP 2019

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 26
      Total Downloads
    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 16 Dec 2024

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media