Multimedia content analysis on gesture event detection for a SMART TV Keyboard application

Enkhtogtokh Togootogtokh, Timothy K. Shih

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We have proposed an effective machine learning method to analyze multimedia content addressing gesture event detection and recognition. Our machine learning method is based on well-studied techniques such that Procrustes Analysis, Combination of Local and Global Representations, Linear Shape Model, and application to SMART TV Virtual Keyboard. In this paper, we address gesture event detection specially fingertip gesture detection to get smart and advanced usage of technology. Our modern vision keyboard could be a good next generation replacement of SMART TV remote control. It can be more economical as we don’t need physical object like traditional keyboard, remote control and their energy resources like batteries. More information and demonstrations of the proposed keyboard can be accessed at http://video.minelab.tw/MCAoGED/.

Original languageEnglish
Pages (from-to)7341-7363
Number of pages23
JournalMultimedia Tools and Applications
Volume76
Issue number5
DOIs
StatePublished - 1 Mar 2017

Keywords

  • Computer vision
  • Gesture event detection
  • Gesture event recognition
  • Machine learning for gesture event detection
  • SMART TV Keyboard

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