IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
권호 표지
DOI QR코드

DOI QR Code

A Novel Human Detection Scheme using a Human Characteristics Function in a Low Resolution 2D LIDAR

저해상도 2D 라이다의 사람 특성 함수를 이용한 새로운 사람 감지 기법

  • Received : 2016.03.31
  • Accepted : 2016.06.13
  • Published : 2016.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

Human detection technologies are widely used in smart homes and autonomous vehicles. However, in order to detect human, autonomous vehicle researchers have used a high-resolution LIDAR and smart home researchers have applied a camera with a narrow detection range. In this paper, we propose a novel method using a low-cost and low-resolution LIDAR that can detect human fast and precisely without complex learning algorithm and additional devices. In other words, human can be distinguished from objects by using a new human characteristics function which is empirically extracted from the characteristics of a human. In addition, we verified the effectiveness of the proposed algorithm through a number of experiments.

Keywords

References

  1. H. Zheng, H. Wang, N. Black, "Human activity detection in smart home environment with self-adaptive neural networks," Proceedings of IEEE International Conference on Networking Sensing Control, pp. 1505-1510, 2008.
  2. C. Premebida, O. Ludwig, U. Nunes, "Exploiting LIDAR-based Features on Pedestrian Detection in Urban Scenarios," Proceedings of 12th International IEEE Conference on Intelligent Transportation Systems, pp. 405-410, 2009.
  3. T. Ogawa, H. Sakai, Y. Suzuki, K. Takagi, K. Morikawa, "Pedestrian detection and tracking using in-vehicle lidar for automotive application," Proceedings of IEEE Intelligent Vehicles Symposium, pp. 734-739, 2011.
  4. K. Kidono , T. Miyasaka, A. Watanabe , T. Naito, J. Miura, "Pedestrian recognition using high-definition LIDAR," Proceedings of IEEE Intelligent Vehicles Symposium, pp. 405-410, 2011.
  5. F. Zhang, D. Clarke, A. Knoll, "Vehicle detection based on lidar and camera fusion," Proceedings of 17th International IEEE Conference on Intelligent Transportation Systems, pp. 1620-1625. 2014.
  6. M. Butenuth, F. Burkert, F. Schmidt, S. Hinz, "Integrating pedestrian simulation, tracking and event detection for crowd analysis," Proceedings of IEEE International Conference on Computer Vision Workshops, pp. 150-157, 2011.
  7. D. Zhang, F. Xia, Z. Yang, L. Yao, W. Zhao, "Localization technologies for indoor human tracking," Proceedings of 5th International Conference on Future Information Technology, pp. 1-6, 2010.
  8. M. Quigley, D. Stavens, A. Coates, and S. Thrun, "Sub-meter indoor localization in unmodified environments with inexpensive sensors," Intelligent Robots and Systems, 2010.
  9. L. Oliveira, U. Nunes, "Context-aware pedestrian detection using lidar." Proceedings of IEEE Intelligent Vehicles Symposium, pp. 773-778. 2010.
  10. C. Premebida , G. Monteiro , U. Nunes, P. Peixoto, "A lidar and vision-based approach for pedestrian and vehicle detection and tracking," Proceedings of IEEE Intelligent Transportation Systems Conference, pp. 1044-1049, 2007.
  11. K.O. Arras, oscar Martinez Mozos, W. Burgard, "Using boosted features for the detection of people in 2d range data," Proceedings of IEEE International Conference on Robotics and Automation, pp. 3402-3407, 2007.
  12. C. Premebida, O. Ludwig, U. Nunes, "Lidar and vision-based pedestrian detection system", Journal of Field Robotics, Vol. 26, No. 9, pp.696-711, 2009. https://doi.org/10.1002/rob.20312
  13. Premebida C, Nunes U, "A Multi-Target Tracking and GMM-Classifier for Intelligent Vehicles," Proceedings of IEEE Intelligent Transportation Systems Conference, pp. 313-318, 2006.
  14. F. Morsdorf, E. Meier, B. Ko,tz, K. Itten, M. Dobbertin, B. Allgo,wer, "LIDAR based geometric reconstruction of broreal type forest stands at single tree level for forest and wildland fire management," Remote Sens. Environ, Vol. 92, No. 3, pp. 353-362, 2004. https://doi.org/10.1016/j.rse.2004.05.013
  15. M. Lee, S. Hur, Y. Park, "Obstacle Classification Method Based on Single 2D LIDAR Database," IEMEK J. Embed. Sys. Appl., Vol. 10, No. 3, pp. 179-188, 2015 (in Korean). https://doi.org/10.14372/IEMEK.2015.10.3.179