Occupant Body Imaging based on Occupancy Grid Mapping

被引：2
|
作者：
Kitamura, Takayuki [1 ]
Kumagai, Taro [1 ]
Takei, Takumi [1 ]
Matsushima, Isao [1 ]
Oishi, Noboru [1 ]
Suwa, Kei [1 ]
机构：
[1] Mitsubishi Electr Corp, Tokyo, Japan
来源：
2021 32ND IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2021年
关键词：
D O I：
10.1109/IV48863.2021.9575618
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents vehicle occupant body imaging algorithms for detecting the presence of children that are left behind in vehicles. The proposed algorithms utilize occupancy grid mapping (OGM) techniques developed for autonomous driving, which are modified for in-cabin human detection purposes. Two different kinds of OGM techniques are presented to deal with two major difficulties in imaging the occupant bodies in an in-cabin environment. The processing flows of the proposed algorithms are detailed in this report. Two experimental results for 60 GHz millimeter-wave radars are also presented for performance verification.
引用
收藏
页码：755 / 761
页数：7
相关论文
共 50 条
  • [1] Improved occupancy grid learning - The ConForM approach to occupancy grid mapping
    Collins, Thomas
    Collins, J. J.
    Ryan, Conor
    [J]. ICINCO 2007: PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL RA-2: ROBOTICS AND AUTOMATION, VOL 2, 2007, : 492 - 497
  • [2] Experimental Comparison of Sonar Based Occupancy Grid Mapping Methods
    Ivanjko, Edouard
    Petrovic, Ivan
    Brezak, Misel
    [J]. AUTOMATIKA, 2009, 50 (1-2) : 65 - 79
  • [3] Indoor Occupancy Grid Mapping Method Based on RGBD Information
    Yan, Da-Yu
    Jing, Gui-Fei
    Yang, Dong-Kai
    Xiu, Chun-Di
    [J]. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 2019, 39 : 68 - 72
  • [4] Probabilistic Robotic Grid Mapping based on Occupancy and Elevation Information
    Souza, Anderson
    Maia, Rosiery S.
    Aroca, Rafael V.
    Goncalves, Luiz M. G.
    [J]. 2013 16TH INTERNATIONAL CONFERENCE ON ADVANCED ROBOTICS (ICAR), 2013,
  • [5] Range Sensor-based Occupancy Grid Mapping with Signatures
    Horvath, Erno
    Hajdu, Csaba
    Radu, Claudiu
    Ballagi, Aron
    [J]. 2019 20TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC), 2019, : 54 - 58
  • [6] Semantical Occupancy Grid Mapping Framework
    Korthals, Timo
    Exner, Julian
    Schoepping, Thomas
    Hesse, Marc
    [J]. 2017 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR), 2017,
  • [7] Occupancy Grid mapping: An empirical evaluation
    Collins, Thomas
    Collins, J. J.
    Ryan, Conor
    [J]. 2007 MEDITERRANEAN CONFERENCE ON CONTROL & AUTOMATION, VOLS 1-4, 2007, : 1592 - 1597
  • [8] Adaptive occupancy grid mapping with clusters
    Jang, Byoung-Gi
    Choi, Tae-Yong
    Lee, Ju-Jang
    [J]. ARTIFICIAL LIFE AND ROBOTICS, 2006, 10 (02) : 162 - 165
  • [9] Feature Based Occupancy Grid Maps for Sonar Based Safe-Mapping
    Pandey, Amit Kumar
    Krishna, K. Madhava
    Nath, Mainak
    [J]. 20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2007, : 2172 - 2177
  • [10] LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping
    Tibebu, Haileleol
    Roche, Jamie
    De Silva, Varuna
    Kondoz, Ahmet
    [J]. SENSORS, 2021, 21 (07)
12345