Simultaneous Multi-View Camera Pose Estimation and Object Tracking with Square Planar Markers
| Autor: | Hamid Sarmadi, Rafael Muñoz-Salinas, Rafael Medina-Carnicer, M. A. Berbís |
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| Přispěvatelé: | [Sarmadi, Hamid] Inst Maimonides Invest Biomed Cordoba, Cordoba 14004, Spain, [Munoz-Salinas, Rafael] Inst Maimonides Invest Biomed Cordoba, Cordoba 14004, Spain, [Medina-Carnicer, R.] Inst Maimonides Invest Biomed Cordoba, Cordoba 14004, Spain, [Munoz-Salinas, Rafael] Univ Cordoba, Dept Informat & Anal Numer, Edificio Einstein,Campus Rabanales, E-14071 Cordoba, Spain, [Medina-Carnicer, R.] Univ Cordoba, Dept Informat & Anal Numer, Edificio Einstein,Campus Rabanales, E-14071 Cordoba, Spain, [Berbis, M. A.] Grp Hlth Time, Cordoba 14012, Spain, Spain Ministry of Economy, Industry and Competitiveness, FEDER |
| Rok vydání: | 2021 |
| Předmět: |
System
FOS: Computer and information sciences 0209 industrial biotechnology General Computer Science Computer science Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition Generation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Augmented reality Tracking (particle physics) 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering camera pose estimation General Materials Science Computer vision Pose robotics business.industry Frame (networking) General Engineering Process (computing) Robotics Object (computer science) augmented reality Video tracking Calibration 020201 artificial intelligence & image processing Artificial intelligence lcsh:Electrical engineering. Electronics. Nuclear engineering business Fiducial markers lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 22927-22940 (2019) |
| DOI: | 10.48550/arxiv.2103.09141 |
| Popis: | Object tracking is a key aspect in many applications such as augmented reality in medicine (e.g. tracking a surgical instrument) or robotics. Squared planar markers have become popular tools for tracking since their pose can be estimated from their four corners. While using a single marker and a single camera limits the working area considerably, using multiple markers attached to an object requires estimating their relative position, which is not trivial, for high accuracy tracking. Likewise, using multiple cameras requires estimating their extrinsic parameters, also a tedious process that must be repeated whenever a camera is moved. This work proposes a novel method to simultaneously solve the above-mentioned problems. From a video sequence showing a rigid set of planar markers recorded from multiple cameras, the proposed method is able to automatically obtain the three-dimensional configuration of the markers, the extrinsic parameters of the cameras, and the relative pose between the markers and the cameras at each frame. Our experiments show that our approach can obtain highly accurate results for estimating these parameters using low resolution cameras. Once the parameters are obtained, tracking of the object can be done in real time with a low computational cost. The proposed method is a step forward in the development of cost-effective solutions for object tracking. Comment: Some errors in the IEEE Access version (regarding object's rotational accuracy, and the definition of Equation 14) have been corrected in this version. IEEE Access paper: https://doi.org/10.1109/ACCESS.2019.2896648 |
| Databáze: | OpenAIRE |
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