From Point Cloud to 3D Print
Object Reconstruktion with RGB and Depth Camera. Mesh Processing and Printer Pre-processing

Structure from Motion

Structure from Motion SFM ist a term from Computer Vision and designates the automated process for detecting spatial structures of objects from corresponding features in images. In Photogrammetry this is also known as multi-image photogrammetry The prodcess is based on BUNDLER, developed at Washington University. The software reconstructs unordered image sequences taken with several cameras. Bundler incoming values are digital images, image features and image correspondencies. The reconstruction provides camera and scene geometry. Bundler is open source software running on Linux and Windows platforms.

Processing steps of Bundler

At the outlet Bundler builds an image list with start values for camera parameter from the EXIF information. The next step detects image features, applying the SIFT detector. The algorithm SIFT (scale invariant keypoint detector) was developed by Loewe at the University of British Columbia in 1999. Matching of the keypoints is done by the RANSAC algorithm. Camera parameter, photo positions and object point co-ordiantes are computed by the least squares method. A sample is given in the figure top right, that displays the 3D model of Konaq-Mosque in Izmir.

BUNDLER extensions are Patch-based Multi-view Stereo PMVS and CMVS Clustering-views for Multi-View Stereo Software from Yasutaka Furukawa, Univ. Washington. CMVS is a pre-processor for PMVS, tiling large image data and PMVS provides a dense point cloud as shown in the lower figure.


Spares point cloud calculated with BUNDLER (left), dense pointcloud computed with PMVS (right)

There are several distributions of SFM software existing. First choice should be VSFM Visual Structure from Motion from Cangchang WU, Univ.Washington, Download from

An alternative to the desktop solutions are the online services, offered by some companies for free. Known and proved solutions are: