A portable three-dimensional LIDAR-based system for long-term and wide-area people behavior measurement

被引:268
作者
Koide, Kenji [1 ,2 ]
Miura, Jun [1 ]
Menegatti, Emanuele [2 ]
机构
[1] Toyohashi Univ Technol, Dept Comp Sci & Informat Engn, Toyohashi, Aichi 4418580, Japan
[2] Univ Padua, Dept Informat Engn, Padua, Italy
关键词
3-D LIDAR; people detection and tracking; behavior analysis; TRACKING; IDENTIFICATION; MODEL;
D O I
10.1177/1729881419841532
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
It is important to measure and analyze people behavior to design systems which interact with people. This article describes a portable people behavior measurement system using a three-dimensional LIDAR. In this system, an observer carries the system equipped with a three-dimensional Light Detection and Ranging (LIDAR) and follows persons to be measured while keeping them in the sensor view. The system estimates the sensor pose in a three-dimensional environmental map and tracks the target persons. It enables long-term and wide-area people behavior measurements which are hard for existing people tracking systems. As a field test, we recorded the behavior of professional caregivers attending elderly persons with dementia in a hospital. The preliminary analysis of the behavior reveals how the caregivers decide the attending position while checking the surrounding people and environment. Based on the analysis result, empirical rules to design the behavior of attendant robots are proposed.
引用
收藏
页数:16
相关论文
共 45 条
  • [31] OpenPTrack: Open source multi-camera calibration and people tracking for RGB-D camera networks
    Munaro, Matteo
    Basso, Filippo
    Menegatti, Emanuele
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2016, 75 : 525 - 538
  • [32] Munaro M, 2014, ADV COMPUT VIS PATT, P161, DOI 10.1007/978-1-4471-6296-4_8
  • [33] Nelson E, 2016, BLAM BERKELEY LOCALI
  • [34] Oishi S, 2016, IEEE ROMAN, P1038, DOI 10.1109/ROMAN.2016.7745236
  • [35] Wearable Smart System for Visually Impaired People
    Ramadhan, Ali Jasim
    [J]. SENSORS, 2018, 18 (03):
  • [36] Features for Multi-Target Multi-Camera Tracking and Re-Identification
    Ristani, Ergys
    Tomasi, Carlo
    [J]. 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, : 6036 - 6046
  • [37] Location tracking system using wearable on-body GPS antenna
    Sabapathy, Thennarasan
    Mustapha, Mohd Amirudin
    Jusoh, Muzammil
    Salleh, Shakhirul Mat
    Soh, Ping Jack
    [J]. ENGINEERING TECHNOLOGY INTERNATIONAL CONFERENCE 2016 (ETIC 2016), 2017, 97
  • [38] Satake J., 2012, Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), P962, DOI 10.1109/ROBIO.2012.6491093
  • [39] Improved boosting algorithms using confidence-rated predictions
    Schapire, RE
    Singer, Y
    [J]. MACHINE LEARNING, 1999, 37 (03) : 297 - 336
  • [40] Biometric gait identification based on a multilayer perceptron
    Semwal, Vijay Bhaskar
    Raj, Manish
    Nandi, G. C.
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2015, 65 : 65 - 75