Extraction and Transfer of Gesture Information using ToF Camera

ToF 카메라를 이용한 제스처 정보의 추출 및 전송

  • 박원창 (한세대학교 IT학부) ;
  • 류대현 (한세대학교 IT학부) ;
  • 최태완 (국립 경남과학기술대학교 메카트로닉스공학과)
  • Received : 2014.08.27
  • Accepted : 2014.10.17
  • Published : 2014.10.31


The latest CCTV camera are network camera in many cases. In this case when transmitting high-quality image by internet, it could be a large load on the internet because the amount of image data is very large. In this study, we propose a method which can reduce the video traffic in this case, and evaluate its performance. We used a method for transmitting and extracting a gesture information using ToF camera such as Kinect in certain circumstances. There may be restrictions on the application of the proposed method because it depends on the performance of the ToF camera. However, it can be applied efficiently to the security or safety management of a small interior space such as a home or office.


Supported by : 경남과학기술대학교


  1. Z. Ren, J. Meng, J. Yuan, and Z. Zhang, "Robust hand gesture recognition with kinect sensor," MM '11 Proc. the 19th ACM Int. Conf. on Multimedia, Scottsdale, AZ, Nov. 2011, pp. 759-760.
  2. C.-S. Won, S.-M. Kim, J.-S. Park, B.-W. Yoon, and J.-K. Song, "Hand Shape Recognition Based on Kinect and Analysis of the Performance," Conf. of the Korean Institute of Electronic Communication Sciences, vol. 7, no 2, Yeosu, Korea, Nov. 2013, pp. 144-147.
  3. S.-M. Kim, J.-K. Song, B.-W. Yoon, and J.-S. Park, "Height Estimation using Kinect in the Indoor," J. of the Korea Institute of Electronic Communication Sciences, vol. 9, no. 3, 2014, pp. 343-350.
  4. J.-S. Park and S.-J. Yi, "Development of Video Data-base and a Video Annotation Tool for Evaluation of Smart CCTV System," J. of the Korea Institute of Electronic Communication Sciences, vol. 9, no. 7, 2014. pp. 739-746.
  5. I.-S. Kim and H. Shin, "A Study on Development of Intelligent CCTV Security System based on BIM," J. of the Korea Institute of Electronic Communication Sciences, vol. 6, no. 5, 2011. pp. 789-795.
  6. S. An, "Face detection and recognition with SURF for human-robot interaction," In Proc. IEEE Int. Conf. on Automation and Logistics, Shenyang, China, Aug. 2009, pp. 1946-1951.
  7. D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int. J. of Computer Vision, vol. 60, no. 2, 2004, pp. 91-110.
  8. H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool, "Surf : Speeded up robust features," Computer Vision and Image Understanding(CVIU), vol. 110, no. 3, 2008, pp. 346-359.
  9. J.-H. Oh, Y. Jung, Y. Cho, C. Hahm, H. Sin, and J. Lee, "Hands-up: Motion Recognition using Kinect and a Ceiling to Improve the Convenience of Human Life," CHI EA '12 Proc. of the 2012 ACM Annual Conf. Extended Abstracts on Human Factors in Computing Systems Extended Abstracts, Austin, TX, May 2012, pp. 1655-1660.