From an image sequence to a recognized polyhedral object

We describe the combination of several novel algorithms into a system which obtains visual motion from a sequence of images and uses it to recover the 3D geometry and 3D motion of polyhedral objects relative to the sensor. The system goes on to use the recovered geometry to recognize the object from a database, a stage which also resolves the depth/speed scaling ambiguity, resulting in absolute depth and motion recovery. We demonstrate its performance of imagery from a well carpentered CSG model and on real imagery from a simple wooden model.