High-resolution Thermopile Array Sensor-based System for Human Detection and Tracking in Indoor Environment

被引:0
作者
Gu, Nanhao [1 ]
Yang, Bo [1 ]
Li, Tianfu [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China
来源
PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020) | 2020年
基金
中国国家自然科学基金;
关键词
Human detection; Tracking; Infrared; Thermopile array sensor;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes an indoor multiple human detection and tracking system based on a high-resolution thermopile array sensor. 'the sensor is deployed at the height of 3m with a vertical downward view. The infrared data of the detection area collected by the sensor is called thermal distribution. The sensor obtains 24x32 pixels thermal distribution. The thermal distribution data is first preprocessed by interpolation and filtering. Then, the background is removed by an adaptive threshold. The high temperature regions and their center points of human targets are obtained by a weighted meanshift method. The thermal feature of a high temperature region is the sum of temperature in the region. Finally, through the space distance and the thermal feature, the center points of high temperature regions are associated with the corresponding human trajectories. Due to the high resolution of thermopile array sensor, the tracking system has a good accuracy, and it can handle the detection and tracking of multiple humans close to each other as well.
引用
收藏
页码:1926 / 1931
页数:6
相关论文
共 9 条
  • [1] Chen WH, 2015, 2015 17TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATION & SERVICES (HEALTHCOM), P428, DOI 10.1109/HealthCom.2015.7454538
  • [2] DESA U., 2017, World population prospects: Key findings and advance tables
  • [3] Multi-Human Locating in Real Environment by Thermal Sensor
    Kuki, Masato
    Nakajima, Hiroshi
    Tsuchiya, Naoki
    Hata, Yutaka
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), 2013, : 4623 - 4628
  • [4] Kuki M, 2012, IEEE SYS MAN CYBERN, P2042, DOI 10.1109/ICSMC.2012.6378039
  • [5] Indoor Region Localization With Asynchronous Sensing Data: A Bayesian Probabilistic Model
    Liang, Weichao
    Wang, Youquan
    Wu, Zhiang
    Mao, Bo
    Cao, Jie
    [J]. IEEE SENSORS JOURNAL, 2018, 18 (24) : 10174 - 10182
  • [6] Simultaneous Indoor Tracking and Activity Recognition Using Pyroelectric Infrared Sensors
    Luo, Xiaomu
    Guan, Qiuju
    Tan, Huoyuan
    Gao, Liwen
    Wang, Zhengfei
    Luo, Xiaoyan
    [J]. SENSORS, 2017, 17 (08)
  • [7] Multiple Human Tracking Using Binary Infrared Sensors
    Miyazaki, Toshiaki
    Kasama, Yuki
    [J]. SENSORS, 2015, 15 (06) : 13459 - 13476
  • [8] Regalado A, 2018, MIT TECHNOL REV, V121, P36
  • [9] A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time
    Wang, Zhihua
    Yang, Zhaochu
    Dong, Tao
    [J]. SENSORS, 2017, 17 (02)