Vision-based raising hand detection in classroom

Cheng Chieh Chiang, Cheng Chuan Tsai, Greg C. Lee

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

Abstract

Raising hand is one of the most important types of interaction between students and lecturers in classroom. When an automatic system can be installed in classroom to figure out which students raise their hands, it is possible to design more advanced applications for education goals. This paper proposes a system that employs computer vision technologies to automatically detect the student action of raising hand. We first design a foreground extraction method to segment student bodies in consecutive video frames. Next, a shape-like appearance signature that represents human gestures is designed based on the scale-invariant feature transform (SIFT) descriptor. A gesture classifier for raising hands is also designed using the support vector machine (SVM) approach. This paper designs several experiments to demonstrate the performance of our proposed system in a real classroom.

Original languageEnglish
Title of host publicationProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013
PublisherMVA Organization
Pages61-64
Number of pages4
ISBN (Print)9784901122139
Publication statusPublished - 2013
Externally publishedYes
Event13th IAPR International Conference on Machine Vision Applications, MVA 2013 - Kyoto, Japan
Duration: 2013 May 202013 May 23

Publication series

NameProceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013

Conference

Conference13th IAPR International Conference on Machine Vision Applications, MVA 2013
CountryJapan
CityKyoto
Period13/5/2013/5/23

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Chiang, C. C., Tsai, C. C., & Lee, G. C. (2013). Vision-based raising hand detection in classroom. In Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013 (pp. 61-64). (Proceedings of the 13th IAPR International Conference on Machine Vision Applications, MVA 2013). MVA Organization.