Minimal Aspect Distortion (MAD) Mosaicing of Long Scenes

  • Authors:

  • Alex Rav-Acha;Giora Engel;Shmuel Peleg

  • Affiliations:

  • School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel 91904;School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel 91904;School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel 91904

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2008

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Abstract

Long scenes can be imaged by mosaicing multiple images from cameras scanning the scene. We address the case of a video camera scanning a scene while moving in a long path, e.g. scanning a city street from a driving car, or scanning a terrain from a low flying aircraft.A robust approach to this task is presented, which is applied successfully to sequences having thousands of frames even when using a hand-held camera. Examples are given on a few challenging sequences. The proposed system consists of two components: (i) Motion and depth computation. (ii) Mosaic rendering.In the first part a "direct" method is presented for computing motion and dense depth. Robustness of motion computation has been increased by limiting the motion model for the scanning camera. An iterative graph-cuts approach, with planar labels and a flexible similarity measure, allows the computation of a dense depth for the entire sequence.In the second part a new minimal aspect distortion (MAD) mosaicing uses depth to minimize the geometrical distortions of long panoramic images. In addition to MAD mosaicing, interactive visualization using X-Slits is also demonstrated.