|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
TOWARDS 3D OBJECT MODEL ACQUISITION AND RECOGNITION USING 3D AFFINE INVARIANTS
Sven Vinther and Roberto Cipolla
We evaluate the power of 3D affine invariants in an object recognition scheme. These invariants are actively calculated by the real-time tracking of 2D image features (corners) over an image sequence. This is done optimally by using a Kalman filter. Object information is located in a hash table where it is stored and retrieved using the invariants as stable indices. Recognition takes place when significant evidence for a particular shape has been found from the table. Preliminary results with real data are presented, and some of the noise problems arising due to the weak perspective approximation and corner localisation errors are discussed.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.
|| Search | CUED | Cambridge University ||
2005 Cambridge University Engineering Dept
Information provided by milab-maintainer