Probabilistic Feature-based On-line Rapid Model Acquisition [Home][2009 BMVC Paper (6.3MB)][BibTeX]
Off-line model reconstruction relies on an image collection phase and a
slow reconstruction phase, requiring a long time to verify a model
obtained from an image sequence is acceptable. We propose a new model
acquisition system, called ProFORMA, which generates a 3D model on-line
as the input sequence is being collected. As the user rotates the
object in front of a stationary camera, a partial model is
reconstructed and displayed to the user to assist view planning. The
model is also used by the system to robustly track the pose of the
object. Models are rapidly produced through a Delaunay
tetrahedralisation of points obtained from on-line structure from
motion estimation, followed by a probabilistic tetrahedron carving step
to obtain a textured surface mesh of the object.
Figure 1: Left to right (a)
Object rotated by hand in front
Point cloud obtained from on-line structure from motion
estimation followed by bundle adjustment. (c) Delaunay
Tetrahedralisation of point cloud, partitioning the convex hull into
Carved mesh obtained from recursive probabilisitic
tetrahedron carving. (e)
Texture-mapped surface mesh.
Figure 2: Results of
reconstruction for various objects.
I am very grateful to Tom Drummond, Gerhard Reitmayr and Ed Rosten for their support, guidance and interesting discussions, as well as various fragments of code.
Many thanks to Ethan Eade for his bundle adjustment and five-point code, without which the first version of this system would not have been possible.
Department of Engineering. University of Cambridge
Trumpington Street, Cambridge CB2 1PZ