|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
EFFECTIVE CORNER MATCHING
P. Smith and D. Sinclair and R. Cipolla and K. Wood
This paper tackles the problem of obtaining a good initial set of corner matches between two images without resorting to any constraints from motion or structure models. Several different matching metrics, both traditional and statistical, are evaluated and the effect of matching using sub-pixel information is studied. It is found that, in most cases, the commonly-used cross-correlation does not perform as well as some other measures, such as the chi squared test or the sum of squared differences, and that it is essential to use sub-pixel accuracy if mismatches are to be avoided.
Further, a new technique, the Median Flow Filter, is introduced. This detects outliers by assuming that the image motion is locally similar. Any matches which are in gross disagreement with the local "median flow" are discarded. Experiments show this technique to be particularly effective, typically lowering the percentage of outliers from around 35% to less than 5%, permitting direct model fitting rather than random sampling techniques for any further analysis.
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