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.
A. Rav-Acha, G. Engel, and S. Peleg, Minimal Aspect Distortion (MAD) Mosaicing of Long Scenes , IJCV, Vol 78, No. 2-3, July 2008, pp. 187-206.
(Click on pictures to enlarge or to view the video)
A Street in Jerusalem
Boat Ride in Germany
Derailed Shinkansen Train