Earticle

초록

영어

We present a method of recognizing hand gestures using RGB values, depth value, hand center coordinates, and finger counting data from Microsoft’s Kinect for implementing the immersive hand interface to overcome inconvenience using HMD. First, we set the RGB values and depth range to detect the hand. This processing can improve recognition rate. Then, through double labeling, outside labeling, and inside labeling, we detect the hand without noise. Then, we use the distance vector to obtain the hand center. It also removes everything except the hand area, including removal of the wrist. After detection of the hand, we use HNMA (Multi Information-Hippocampus Neuron Modeling Algorithm) to recognize the hand gesture. This algorithm helps to improve the recognize rate. It is difficult to use the interface when using an HMD (Head Mount Display) display machine. This algorithm can make an immersive environment.

목차

Abstract
 1. Introduction
 2. Background Theory
  2.1. Hand Detection Based on Kinect
  2.2. Hippocampus Neuron Modeling Theory
 3. Proposed Algorithm
  3.1. Hand Detection Processing
  3.2. Learning Algorithm Setting
  3.3. Experimental Results Disseminate
 4. Conclusion and Future Research
 Acknowledgment
 References

키워드

저자

• Gi-Woo Kim [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]
• Hye-Youn Lim [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]
• Dae-Seong Kang [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605