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Random Forest Based Gesture Segmentation from Depth Image

  • Renjun Tang
  • Hang Pan
  • Xianjun ChenEmail author
  • Jinlong Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10942)

Abstract

Gesture image segmentation is a challenge task due to the high degree of freedom of human gestures, large differences in shape and high flexibility, traditional pattern recognition and image processing methods are not effective in gesture detection. The traditional image segmentation based on the detection of skin color and the image of the depth image are limited by the effects of ambient light, skin color difference and image depth variation, resulting in unsatisfactory results. Therefore, we propose a hand gesture depth image segmentation method based on random forest. The method learns the gesture image feature representation of the depth image by supervising learning. Experiments show that the proposed method segments the gesture s’ pixels from the backgrounds area of the depth image. The proposed method potential has widely usages in gesture tracking, gesture recognition and human computer interaction.

Keywords

Random forest Gesture segmentation Depth image 

Notes

Acknowledgments

This research work is supported by the grant of Guangxi science and technology development project (No: AC16380124), the grant of Guangxi Science Foundation (No: 2017GXNSFAA198226), the grant of Guangxi Key Laboratory of Trusted Software of Guilin University of Electronic Technology (No: KX201513), the grant of Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics of Guilin University of Electronic Technology (No: GIIP201602), and the grant of Innovation Project of GUET Graduate Education (2018YJCX43).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Renjun Tang
    • 1
    • 2
  • Hang Pan
    • 1
  • Xianjun Chen
    • 1
    • 3
    Email author
  • Jinlong Chen
    • 2
  1. 1.Guangxi Key Laboratory of Trusted SoftwareGuilin University of Electronic TechnologyGuilinChina
  2. 2.Key Laboratory of Intelligent Processing of Computer Image and GraphicsGuilin University of Electronic TechnologyGuilinChina
  3. 3.Information Engineering School, Haikou College of EconomicsHaikouChina

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