Minimal Aspect Distortion (MAD) mosaicing of long scenes

Alex Rav-Acha, Giora Engel, Shmuel Peleg*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

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.

Original languageEnglish
Pages (from-to)187-206
Number of pages20
JournalInternational Journal of Computer Vision
Volume78
Issue number2-3
DOIs
StatePublished - Jul 2008

Keywords

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

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