Multimedia Tools and Applications

, Volume 76, Issue 5, pp 7341–7363 | Cite as

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

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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/.

Keywords

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

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.MINE Lab, Department of Computer Science and Information EngineeringNational Central University (NCU)Jhongli City, Taoyuan CountyChina

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