image/svg+xml SfM Workflow Acquire Imagery SIFT Scale InvariantFeature Transform Find matching pointsin multiple images CMVS & PMVS Clustering View forMultiview Stereo Dense pointcloud Bundle Adjustment Sparse point cloud &estimate camera position A Structure from Motionapproach to image processing Big Data& Photogrammetry TraditionalPhotogrammetry Metric Cameras: - focal length- aperture- stable film plane- lens corrected- flying height- relies on GCPs Structurefrom Motion Big Data approach: - camera position and settings, and scene geometry are computed simultaneously in a recursive process that identifies matching features in multiple images.- GCPs improve accuracy. Structure from Motion (SfM) Digital image matching algorithms- 1980s (F rstner, 1986)Computer Vision research- early 1990s (Spetsakis and Aloimonos, 1991)Mature SfM approaches - mid 2000s(Furukawa and Ponce, 2007) ö Westoby, M.J., Brasington, J., Glasser, N.F., Hambrey, M.J., and Reynolds, J.M.2012. 'Structure-from-Motion' photogrammetry: A low-cost, effective tool for geoscience applications. 1 179, 300-314.
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