Pose estimation using polarimetric imaging in low-light environment

被引:0
|
作者
Wan, Zhenhua [1 ]
Zhao, Kaichun [2 ]
Chu, Jinkui [1 ]
机构
[1] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
[2] Tsinghua Univ, Dept Precis Instrument, Beijing 100084, Peoples R China
关键词
pose estimation; polarimetric imaging; low-light environment; STEREO;
D O I
10.1117/12.2617518
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Visual pose estimation is of great significance in the field of precision measurement and navigation and positioning. However, under low-light illumination conditions, the feature extraction of traditional visual images is easy to fail, resulting in the failure of visual pose estimation. This paper proposes a pose estimation method based on polarimetric imaging under low-light illumination conditions. This method calculates the polarization information of the target environment and uses the polarization image to calculate the pose. Since the degree of polarization can highlight the contour of the target, this method combines the advantages of the polarization characteristics of the target environment to estimate the pose. Through environmental experiments, we found that the grayscale distribution of the polarization image is more uniform in the low-light environment, and the grayscale does not change significantly with the illumination. We verified the feasibility of the proposed posture estimation method based on polarimetric imaging. This method provides a technical reference for special scenarios (tunnels, underground parking lots).
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Human Pose Estimation in Extremely Low-Light Conditions
    Lee, Sohyun
    Rim, Jaesung
    Jeong, Boseung
    Kim, Geonu
    Woo, Byungju
    Lee, Haechan
    Cho, Sunghyun
    Kwak, Suha
    [J]. 2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR, 2023, : 704 - 714
  • [2] Pose Estimation of Unresolved Targets using Polarimetric Imaging
    Gartley, Michael
    Erbach, Peter
    Pezzaniti, Larry
    [J]. POLARIZATION: MEASUREMENT, ANALYSIS, AND REMOTE SENSING IX, 2010, 7672
  • [3] LOW-LIGHT LEVEL IMAGING
    VANALLER, G
    KUHL, W
    [J]. ACTA ELECTRONICA, 1977, 20 (03): : 231 - 239
  • [4] LOW-LIGHT ENVIRONMENT NEURAL SURVEILLANCE
    Potter, Michael
    Gridley, Henry
    Lichtenstein, Noah
    Hines, Kevin
    Nguyen, John
    Walsh, Jacob
    [J]. PROCEEDINGS OF THE 2020 IEEE 30TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2020,
  • [5] Active and Low-Cost Hyperspectral Imaging for the Spectral Analysis of a Low-Light Environment
    Tang, Yang
    Song, Shuang
    Gui, Shengxi
    Chao, Weilun
    Cheng, Chinmin
    Qin, Rongjun
    [J]. SENSORS, 2023, 23 (03)
  • [6] Gaze in the Dark: Gaze Estimation in a Low-Light Environment with Generative Adversarial Networks
    Kim, Jung-Hwa
    Jeong, Jin-Woo
    [J]. SENSORS, 2020, 20 (17) : 1 - 20
  • [7] Low-light imaging with SPAD pixels
    Stuart Thomas
    [J]. Nature Electronics, 2021, 4 : 862 - 862
  • [8] Low-light imaging with SPAD pixels
    Thomas, Stuart
    [J]. NATURE ELECTRONICS, 2021, 4 (12) : 862 - 862
  • [9] Camera selection for low-light imaging
    Asche, Felix
    [J]. Asche, Felix, 1600, Laurin Publishing Co. Inc. (55): : 46 - 53
  • [10] Low-Light Reflective Correlation Imaging
    Akhlaghi-Bouzan, Milad
    Kohlgraf-Owens, Thomas
    Dogariu, Aristide
    [J]. 2015 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), 2015,