A new camera model for higher accuracy pose calculations

被引:4
|
作者
Ryberg, Anders [1 ]
Christiansson, A-K [1 ]
Eriksson, K. [1 ]
Lennartson, Bengt [2 ]
机构
[1] Univ West, Dept Technol Math & Comp Sci, SE-46186 Trollhattan, Sweden
[2] Chalmers, SE-41296 Gothenburg, Sweden
关键词
D O I
10.1109/ISIE.2006.296058
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A position and orientation (pose) measurement system is being developed. The system, called PosEye, is based on a camera and by using the information in the image, the pose of the camera taking the image can be calculated. The system is aimed to be placed on an industrial robot for welding, but it is flexible and can also be used in many other applications. The accuracy has been measured, see [51, and it is concluded that the accuracy needs to be improved for welding applications. To make the pose measurement, reference points, that can be recognized in the image, are distributed in the working area. The positions of the reference points and the parameters in a camera model are initially computed automatically from sample images from a number of directions to the reference points. After this calibration, the pose can be calculated at each sample image. For high accuracy there is a need to have a camera model that takes into account a number of distortion effects, which are further developed in this paper. The new model is used to express an optimization cost function that can be used for both the pose calculation, and the extensive calibration, that determines camera parameters in the camera model and the positions of the reference points.
引用
收藏
页码:2798 / +
页数:2
相关论文
共 50 条
  • [21] CAMERA CALIBRATION WITH POSE GUIDANCE
    Ren, Yuzhuo
    Hu, Feng
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 2180 - 2184
  • [22] Hybrid Camera Pose Estimation
    Camposeco, Federico
    Cohen, Andrea
    Pollefeys, Marc
    Sattler, Torsten
    2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, : 136 - 144
  • [23] Updating Human Pose Estimation using Event-based Camera to Improve Its Accuracy
    Otake, Ippei
    Kitano, Kazuya
    Kushida, Takahiro
    Kubo, Hiroyuki
    Maejima, Akinobu
    Fujimura, Yuki
    Funatomi, Takuya
    Mukaigawa, Yasuhiro
    PROCEEDINGS OF SIGGRAPH 2023 POSTERS, SIGGRAPH 2023, 2023,
  • [24] Distributed Consensus on Camera Pose
    Jorstad, Anne
    DeMenthon, Daniel
    Wang, I-Jeng
    Burlina, Philippe
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (09) : 2396 - 2407
  • [25] Accuracy Evaluation of 3D Pose Reconstruction Algorithms Through Stereo Camera Information Fusion for Physical Exercises with MediaPipe Pose
    Dill, Sebastian
    Ahmadi, Arjang
    Grimmer, Martin
    Haufe, Dennis
    Rohr, Maurice
    Zhao, Yanhua
    Sharbafi, Maziar
    Hoog Antink, Christoph
    Sensors, 2024, 24 (23)
  • [26] ASSESSING THE ACCURACY OF MIXTURE MODEL REGRESSION CALCULATIONS
    SNEE, RD
    RAYNER, AA
    JOURNAL OF QUALITY TECHNOLOGY, 1982, 14 (02) : 67 - 79
  • [27] Accuracy of Cluster Model Calculations for Quasicrystal Surface
    Sato, Masanori
    Hiroto, Takanobu
    Matsushita, Yoshitaka
    Nozawa, Kazuki
    MATERIALS TRANSACTIONS, 2021, 62 (03) : 350 - 355
  • [28] Multi-Camera Rigid Body Pose Estimation using Higher Order Dynamic Models
    Forsman, Alec E.
    Schug, David A.
    Haug, Anton J.
    AUTOMATIC TARGET RECOGNITION XXIII, 2013, 8744
  • [29] Higher Accuracy Achieved for Protein-Ligand Binding Pose Prediction by Elastic Network Model-Based Ensemble Docking
    Wang, Anhui
    Zhang, Yuebin
    Chu, Huiying
    Liao, Chenyi
    Zhang, Zhichao
    Li, Guohui
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2020, 60 (06) : 2939 - 2950
  • [30] Camera Pose Estimation using Human Head Pose Estimation
    Fischer, Robert
    Hoedlmoser, Michael
    Gelautz, Margrit
    PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 4, 2022, : 877 - 886