, HUJI, School of Computer Science and Engineering, CS - Computer Vision
Long scenes can be imaged by far away cameras, or by mosaicing multiple images from closer 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 new minimal aspect distortion (MAD) mosaicing of the long scene is presented, which uses depth to minimize the geometrical distortions and to improve stitching of long panoramic images. We also present a robust ”direct” method to provide both camera motion and dense depth. A limited motion model of a scanning camera is used to increase robustness of motion computation. Iterative graph-cuts, with planar labels and a flexible similarity measure, is used for depth computation.
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Granted US 8,593,506