• DocumentCode
    3572407
  • Title

    Robust Frame Registration for Multiple Camera Setups in Dynamic Scenes

  • Author

    Xu Zhao ; Zhong Zhou ; Ye Duan ; Wei Wu

  • Volume
    1
  • fYear
    2012
  • Firstpage
    373
  • Lastpage
    380
  • Abstract
    In this paper, we propose a novel method to register frames from multiple cameras into a consistent global scale. Assuming a moving object is observed in multiple camera setups, we use initial frames to create a global reference structure where the pose variation of each new frame is estimated using a RANSAC-based registration algorithm. We further combine the registration method with other state-of the-art techniques to build a high quality 3D reconstruction system with a smaller number of cameras than used by more traditional methods. Experimental results show that our method performs better and is more economical than the registration of separate monocular structures from motion methods. 3D reconstruction results on various challenging real world multi-camera video datasets also illustrate the feasibility and robustness of our method.
  • Keywords
    cameras; image motion analysis; image registration; statistical analysis; RANSAC-based registration algorithm; dynamic scenes; global reference structure; high quality 3D reconstruction system; moving object; multiple camera setups; pose variation; real-world multicamera video datasets; robust frame registration; separate monocular structures registration; Cameras; Image reconstruction; Registers; Solid modeling; Stereo image processing; Surface reconstruction; Three-dimensional displays; Bundle Adjustment; Frame Registration; Multiple Camera Setups;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2012 IEEE 24th International Conference on
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4799-0227-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2012.58
  • Filename
    6495070