Minimal Aspect Distortion (MAD) Mosaicing of Long Scenes

  • Alex Rav-Acha
  • Giora Engel
  • Shmuel Peleg


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.


Video mosaicing Ego motion Stereo Panorama X-slits Multi-perspective 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Alex Rav-Acha
    • 1
  • Giora Engel
    • 1
  • Shmuel Peleg
    • 1
  1. 1.School of Computer Science and EngineeringThe Hebrew University of JerusalemJerusalemIsrael

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