Knowledge Base

Home  Search   Show all  Top

Details of the record

titleA performance evaluation of local descriptors
authorsK. Mikolajczyk, C. Schmid
keywordsobject recognition
abstractIn this paper we compare the performance of interest point descriptors. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how their performance depends on the interest point detector. The descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the point detector. Our evaluation uses as criterion detection rate with respect to false positive rate and is carried out for different image transformations. We compare SIFT descriptors [11], steerable filters [5], differential invariants [10], complex filters [17], moment invariants [21] and cross-correlation for different types of interest points [8, 11, 13, 14]. In this evaluation, we observe that the ranking of the descriptors does not depend on the point detector and that SIFT descriptors perform best. Steerable filters come second ; they can be considered a good choice given the low dimensionality.
typeJournal Paper
published year2003
(Total records:1429)
Home  Search   Show all  Top

Powered by: DaDaBIK