International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
권호 표지
DOI QR코드

DOI QR Code

Development of People Counting Algorithm using Stereo Camera on NVIDIA Jetson TX2

  • Lee, Gyucheol (Department of Electronic Engineering, Kwangwoon University) ;
  • Yoo, Jisang (Department of Electronic Engineering, Kwangwoon University) ;
  • Kwon, Soonchul (Graduation School of Smart Convergence, Kwangwoon University)
  • Received : 2018.06.18
  • Accepted : 2018.06.30
  • Published : 2018.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

In the field of surveillance cameras, it is possible to increase the people detection accuracy by using depth information indicating the distance between the camera and the object. In general, depth information is obtained by calculating the parallax information of the stereo camera. However, this method is difficult to operate in real time in the embedded environment due to the large amount of computation. Jetson TX2, released by NVIDIA in March 2017, is a high-performance embedded board with a GPU that enables parallel processing using the GPU. In this paper, a stereo camera is installed in Jetson TX2 to acquire depth information in real time, and we proposed a people counting method using acquired depth information. Experimental results show that the proposed method had a counting accuracy of 98.6% and operating in real time.

Keywords

References

  1. NVIDIA Jetson TX2 Module. https://developer.nvidia.com/embedded/buy/jetson-tx2
  2. T. Darrell, D. Demirdjian, Neal. Checka, and P. Felzenszwalb, "Plan-view Trajectory Estimation with Dense Stereo Background Models," Proceedings of the International, Conference on Computer Vision, Vol. 2, July 2001. DOI: 10.1109/ICCV.2001.937685
  3. Brown, R. Grover, and P. YC Hwang, Introduction to Random Signals and Applied Kalman Filtering, New York: Wiley, pp. 400, 1992.
  4. J. Weng, P. Cohen, and M. Herniou, "Camera Calibration with Distortion Models and Accuracy Evaluation," IEEE Transactions on pattern analysis and machine intelligence, Vol. 14, No. 10, pp. 965-980, Oct 1992. DOI: 10.1109/34.159901
  5. A. Fusiello, E. Trucco, and A. Verri, "A Compact Algorithm for Rectification of Stereo Pairs," Machine Vision and Applications, Vol. 12, No. 1, pp. 16-22, Mar 2000. DOI: https://doi.org/10.1007/s001380050120
  6. G. Bradski, and A. Kaehler, Learning OpenCV: Computer vision with the OpenCV library, O'Reilly Media, pp. 555, 2008.
  7. H. Hirschmuller, "Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, July 2005. DOI: 10.1109/CVPR.2005.56
  8. J. Krumm, S. Harris, B. Meyers, B. Brumitt, M. Hale, and S. Shafer, "Multi-Camera Multi-Person Tracking for EasyLiving," Proceedings Third IEEE International Workshop on Visual Surveillance, July 2000. DOI: 10.1109/VS.2000.856852
  9. Axis People Counter. https://www.axis.com/ko-kr/products/axis-people-counter
  10. Y.H. Hong, S.J. Song, and J. Rho, "Real-time Tracking and Identification for Multi-Camera Surveillance System," International Journal of Internet, Broadcasting and Communication(IJIBC), Vol.10, No.1, pp. 16-22, 2018.
  11. Martins, H. A., J. R. Birk, and R. Bo Kelley. "Camera models based on data from two calibration planes." Computer Graphics and Image Processing 17.2 (1981): 173-180. https://doi.org/10.1016/0146-664X(81)90024-1