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Person Tracking Using ANKLE‐LEVEL LIDAR Based on Enhanced DBSCAN and OPTICS

IEEJ transactions on electrical and electronic engineering, v.16 no.5, 2021년, pp.778 - 786  

Hasan, Mahmudul (HCI Lab Saitama University Saitama Japan) ,  Hanawa, Junichi (HCI Lab Saitama University Saitama Japan) ,  Goto, Riku (HCI Lab Saitama University Saitama Japan) ,  Fukuda, Hisato (HCI Lab Saitama University Saitama Japan) ,  Kuno, Yoshinori (HCI Lab Saitama University Saitama Japan) ,  Kobayashi, Yoshinori (HCI Lab Saitama University Saitama Japan)

Abstract AI-Helper 아이콘AI-Helper

AbstractAlong with the progress of deep learning techniques, people tracking using video cameras became easy and accurate. However, privacy and security issues are not enough to be concerned with vision‐based monitoring. People may not be tolerated surveillance cameras installed everywhere in...

참고문헌 (20)

  1. 10.1007/978-0-387-93808-0_3 

  2. Devarakota, P.R., Castillo-Franco, M., Ginhoux, R., Mirbach, B., Kater, S., Ottersten, B.. 3-D-Skeleton-Based Head Detection and Tracking Using Range Images. IEEE transactions on vehicular technology, vol.58, no.8, 4064-4077.

  3. 10.1109/CVPR.2016.148 McLaughlinN RinconJMDandMillerP.Recurrent convolutional network for video‐based person re‐identification. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Las Vegas NV 2016;1325-1334. 

  4. 10.1109/CVPRW.2019.00106 RobertoHenschel TimovonMarcardandBodoRosenhahn.Simultaneous identification and tracking of multiple people using video and IMUs. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019. 

  5. 10.1109/WPNC.2012.6268761 KöppeE BartholmaiM LiersAandSchillerJ.Radio‐based multi‐sensor system for person tracking and indoor positioning. Proceedings of ninth Workshop on Positioning Navigation and Communication Dresden 2012;180-186. 

  6. Gai, Wei, Qi, Meng, Ma, Mingcong, Wang, Lu, Yang, Chenglei, Liu, Juan, Bian, Yulong, de Melo, Gerard, Liu, Shijun, Meng, Xiangxu. Employing Shadows for Multi-Person Tracking Based on a Single RGB-D Camera. Sensors, vol.20, no.4, 1056-.

  7. 10.1109/CVPR.2008.4587615 ChristoudiasCM UrtasunRandDarrellT.Unsupervised feature selection via distributed coding for multi‐view object recognition. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Anchorage AK;2008 1-8. 

  8. 10.1109/CVPRW.2014.41 KumarS MarksTKandJonesM.Improving person tracking using an inexpensive thermal infrared sensor. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Columbus OH 2014;217-224 

  9. Benedek, Csaba, Gálai, Bence, Nagy, Balázs, Jankó, Zsolt. Lidar-Based Gait Analysis and Activity Recognition in a 4D Surveillance System. IEEE transactions on circuits and systems for video technology : a publication of the Circuits and Systems Society, vol.28, no.1, 101-113.

  10. MEster H‐PKriegel JSanderandXXu.A density‐based algorithm for discovering clusters in large spatial databases with noise. Proceedings of Second International Conference on Knowledge Discovery and Data Mining (KDD'96) AAAI Press 1996;226-231. 

  11. 10.1109/ICRA.2011.5980567 RusuRBandCousinsS.3D is here: Point cloud library (PCL). Proceedings of IEEE International Conference on Robotics and Automation Shanghai 2011;1-4. 

  12. Wang, Chunxiao, Ji, Min, Wang, Jian, Wen, Wei, Li, Ting, Sun, Yong. An Improved DBSCAN Method for LiDAR Data Segmentation with Automatic Eps Estimation. Sensors, vol.19, no.1, 172-.

  13. Hollaus, M., Wagner, W., Eberhöfer, C., Karel, W.. Accuracy of large-scale canopy heights derived from LiDAR data under operational constraints in a complex alpine environment. ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS), vol.60, no.5, 323-338.

  14. Niemeyer, J., Rottensteiner, F., Soergel, U.. Contextual classification of lidar data and building object detection in urban areas. ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing (ISPRS), vol.87, 152-165.

  15. 10.1007/978-3-642-37456-2_14 Campello RJGB DMoulaviandJSander.Density‐based clustering based on hierarchical density estimates. Proceedings of Pacific‐Asia Conference on Knowledge Discovery and Data Mining Springer Berlin Heidelberg 2013. 

  16. 10.1007/978-3-030-51328-3_7 HasanM HanawaJ GotoR FukudaH KunoYandKobayashiY.Tracking people using ankle‐level 2D LiDAR for gait analysis. Advances in Artificial Intelligence Software and Systems Engineering AHFE 2020. Advances in Intelligent Systems and Computing vol 1213 Springer Cham 2020 

  17. Amini, Amineh, Wah, Teh Ying, Saboohi, Hadi. On Density-Based Data Streams Clustering Algorithms: A Survey. Journal of computer science and technology, vol.29, no.1, 116-141.

  18. 10.1109/IROS.2016.7759050 BogoslavskyiIandStachnissC.Fast range image‐based segmentation of sparse 3d laser scans for online operation. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016;163-169. 

  19. 10.1109/ICRA.2017.7989591 ZermasD IzzatIandPapanikolopoulosN.Fast segmentation of 3D point clouds: A paradigm on LiDAR data for autonomous vehicle applications. Proceedings of IEEE international conference on robotics and automation (ICRA) Singapore 2017;5067-5073 

  20. Yan, Zhi, Duckett, Tom, Bellotto, Nicola. Online learning for 3D LiDAR-based human detection: experimental analysis of point cloud clustering and classification methods. Autonomous robots, vol.44, no.2, 147-164.

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