Vision-based Context and Height Estimation for 3D Indoor Location

被引:0
|
作者
Kazemipur, Bashir [1 ,2 ]
Syed, Zainab [2 ]
Georgy, Jacques [2 ]
El-Sheimy, Naser [1 ]
机构
[1] Trusted Positioning Inc, Calgary, AB, Canada
[2] Univ Calgary, Dept Geomat Engn, Calgary, AB, Canada
关键词
computer vision; indoor navigation; sensor fusion; NAVIGATION; IMAGE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Today's smartphones are powerful devices whose continually increasing processing power and wide array of sensors make them well suited for use as personal navigation devices. In the absence of information from the Global Navigation Satellite System (GNSS), the onboard inertial sensors can be used to provide a relative navigation solution. However, these onboard inertial sensors suffer from the effects of different sensor errors which cause the inertial-only solution to deteriorate rapidly. As such, there is a need to constrain the inertial positioning solution when long term navigation is needed. GNSS positions and velocities, and WiFi positions are the most important forms of updates available for the inertial solution. However, updates from these two sources depend on external signals and may not always be available. A rich source of information about the outside world can be obtained using the device's camera. Nearly all devices have at least one camera which has thus far been largely neglected as a navigation aid for these mobile devices. There are many indoor scenarios that require accurate height estimates. Traditionally, barometers have been used to provide height information. However, not all mobile devices that are equipped with inertial sensors are also equipped with a barometer. As nearly all devices are equipped with at least one camera, it is our aim to use information from the camera to aid the inertial-only solution with appropriate height estimates. Different pattern analysis techniques are used to identify the different scenarios. The results are presented for the following common use cases: (1) single floor texting mode, (2) stairs texting mode, (3) single floor calling mode, (4) stairs calling mode, and (5) fidgeting the phone while standing still on a single floor (i.e. "fidgeting"). For each of these use cases, first the context will be determined and then the relevant information will be used to calculate the height accordingly. This work is patent pending.
引用
收藏
页码:1336 / 1342
页数:7
相关论文
共 50 条
  • [31] Neural vision-based semantic 3D world modeling
    Papadopoulos, Sotirios
    Mademlis, Ioannis
    Pitas, Ioannis
    2021 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS (WACVW 2021), 2021, : 181 - 190
  • [32] A Comprehensive Review of Vision-Based 3D Reconstruction Methods
    Zhou, Linglong
    Wu, Guoxin
    Zuo, Yunbo
    Chen, Xuanyu
    Hu, Hongle
    SENSORS, 2024, 24 (07)
  • [33] A parallel stereo vision-based 3D pneumatic arm
    Wang, Ying T.
    Wong, Ray-Hwa
    Liu, Chao-Yi
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2011, 33 (05) : 542 - 557
  • [34] Overview on Vision-Based 3D Object Recognition Methods
    Dong, Tianzhen
    Qi, Xiao
    Zhang, Qing
    Li, Wenju
    Xiong, Liang
    IMAGE AND GRAPHICS, ICIG 2019, PT II, 2019, 11902 : 243 - 254
  • [35] Vision-based 3D scene analysis for driver assistance
    Burschka, D
    Hager, GD
    2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, 2005, : 812 - 818
  • [36] Image Matching Techniques for Vision-based Indoor Navigation Systems: Performance Analysis for 3D Map Based Approach
    Li, Xun
    Wang, Jinling
    2012 INTERNATIONAL CONFERENCE ON INDOOR POSITIONING AND INDOOR NAVIGATION (IPIN), 2012,
  • [37] 3D Vision-based Security Monitoring for Railroad Stations
    Park, Youngtae
    Lee, Daeho
    JOURNAL OF THE OPTICAL SOCIETY OF KOREA, 2010, 14 (04) : 451 - 457
  • [38] Vision-based Indoor Positioning Method By Joint Using 2D Images and 3D Point Cloud Map
    Ma, Lin
    Jiang, Han
    Qin, Danyang
    Tan, Xuezhi
    2020 16TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE, IWCMC, 2020, : 1679 - 1684
  • [39] A real-time vision-based 3D motion estimation system for positioning and trajectory following
    Negahdaripour, S
    Jin, L
    Xu, X
    Tsukamoto, C
    Yuh, J
    THIRD IEEE WORKSHOP ON APPLICATIONS OF COMPUTER VISION - WACV '96, PROCEEDINGS, 1996, : 264 - 269
  • [40] Vision-Based Heading and Lateral Deviation Estimation for Indoor Navigation of a Quadrotor
    Balasubramanian, Anbarasu
    Ganesan, Anitha
    IETE JOURNAL OF RESEARCH, 2017, 63 (04) : 597 - 603