Kinect-based mid-air handwritten digit recognition using multiple segments and scaled coding

Fu An Huang, Chung Yen Su, Tsai Te Chu

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

8 Citations (Scopus)

Abstract

Human-computer interaction has attracted much attention in recent years, especially in the field of entertainment. In our previous study, we presented an effective method of Kinect-based mid-air handwritten digit recognition for a potential application to TV remote controllers. However, its recognition accuracy is only about 86.7%. In this study, we propose an improved method, based on multiple segments and scaled coding. Experimental results show that the proposed method can elevate the accuracy up to 94.6%.

Original languageEnglish
Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
Pages694-697
Number of pages4
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013 - Naha, Okinawa, Japan
Duration: 2013 Nov 122013 Nov 15

Publication series

NameISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems

Other

Other2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013
CountryJapan
CityNaha, Okinawa
Period2013/11/122013/11/15

Keywords

  • Kinect
  • hand gesture recognition
  • handwritten digit recognition
  • human-computer interaction
  • support vector machine

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing

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