Learning-based video fast-pan detection

Hsin Cheng Lin*, Szu-Hao Huang, Shang Hong Lai

*Corresponding author for this work

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

Abstract

In this paper, we introduce the fast-pan detection problem which aims to find out the fast motion / low resolution frames caused by fast camera pan. In addition, we propose an algorithm that employs neural network training process to accomplish the detection. The features used in the neural network process include motion features and texture features. In addition, we also take temporal information into account for determining fast-pan events. Experimental results show that the proposed method which combines motion and texture features could achieve satisfactory performance.

Original languageEnglish
Title of host publicationITRE 2005 - 3rd International Conference on Information Technology
Subtitle of host publicationResearch and Education - Proceedings
Pages181-185
Number of pages5
DOIs
StatePublished - 1 Dec 2005
EventITRE 2005 - 3rd International Conference on Information Technology: Research and Education - Hsinchu, Taiwan
Duration: 27 Jun 200530 Jun 2005

Publication series

NameITRE 2005 - 3rd International Conference on Information Technology: Research and Education - Proceedings
Volume2005

Conference

ConferenceITRE 2005 - 3rd International Conference on Information Technology: Research and Education
CountryTaiwan
CityHsinchu
Period27/06/0530/06/05

Keywords

  • Fast pan
  • Motion estimation
  • Motion feature
  • Motion magnitude
  • Neural network
  • Sobel magnitude

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  • Cite this

    Lin, H. C., Huang, S-H., & Lai, S. H. (2005). Learning-based video fast-pan detection. In ITRE 2005 - 3rd International Conference on Information Technology: Research and Education - Proceedings (pp. 181-185). [1503095] (ITRE 2005 - 3rd International Conference on Information Technology: Research and Education - Proceedings; Vol. 2005). https://doi.org/10.1109/ITRE.2005.1503095