Object detection oriented feature pooling for video semantic indexing

Kazuya Ueki, Tetsunori Kobayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We propose a new feature extraction method for video semantic indexing. Conventional methods extract features densely and uniformly across an entire image, whereas the proposed method exploits the object detector to extract features from image windows with high objectness. This feature extraction method focuses on "objects." Therefore, we can eliminate the unnecessary background information, and keep the useful information such as the position, the size, and the aspect ratio of a object. Since these object detection oriented features are complementary to features from entire images, the performance of video semantic indexing can be further improved. Experimental comparisons using large-scale video dataset of the TRECVID benchmark demonstrated that the proposed method substantially improved the performance of video semantic indexing.

Original languageEnglish
Title of host publicationVISAPP
EditorsFrancisco Imai, Alain Tremeau, Jose Braz
PublisherSciTePress
Pages44-51
Number of pages8
ISBN (Electronic)9789897582264
DOIs
Publication statusPublished - 2017
Event12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017 - Porto, Portugal
Duration: 2017 Feb 272017 Mar 1

Publication series

NameVISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Volume5

Other

Other12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017
CountryPortugal
CityPorto
Period17/2/2717/3/1

Keywords

  • Convolutional neural network
  • Object detection
  • Video retrieval
  • Video semantic indexing

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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  • Cite this

    Ueki, K., & Kobayashi, T. (2017). Object detection oriented feature pooling for video semantic indexing. In F. Imai, A. Tremeau, & J. Braz (Eds.), VISAPP (pp. 44-51). (VISIGRAPP 2017 - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications; Vol. 5). SciTePress. https://doi.org/10.5220/0006099600440051