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Depth and RGB image alignment for hand gesture segmentation using kinect

  • Zhaojie Jul*
  • , Yuehui Wang
  • , Wei Zeng
  • , Shengyong Chen
  • , Honghai Liu
  • *Corresponding author for this work
  • University of Portsmouth
  • Zhejiang University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a novel method for the depth map and RGB image alignment for Kinect. Genetic algorithm is used to estimate the key points from both depth and RGB images, and this method is robust to the uncertainties of the extracted point numbers. The experimental results demonstrated that the proposed method is capable of precisely aligning the depth and RGB images, contributes a great improvement for hand gesture segmentation, and will potentially improve the performance of hand gesture recognition in Human-Computer Interaction (HCI).

Original languageEnglish
Title of host publicationProceedings - International Conference on Machine Learning and Cybernetics
PublisherIEEE Computer Society
Pages913-919
Number of pages7
ISBN (Electronic)9781479902576
DOIs
StatePublished - 2013
Externally publishedYes
Event12th International Conference on Machine Learning and Cybernetics, ICMLC 2013 - Tianjin, China
Duration: 14 Jul 201317 Jul 2013

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume2
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference12th International Conference on Machine Learning and Cybernetics, ICMLC 2013
Country/TerritoryChina
CityTianjin
Period14/07/1317/07/13

Keywords

  • Alignment
  • Calibration
  • Depth Camera
  • HCI
  • Hand Gesture Recognition

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