@inproceedings{a33672a7fba24a84ac514ab5953dca0c,
title = "Evaluation of salient point techniques",
abstract = "In image retrieval, global features related to color or texture are commonly used to describe the image content. The problem with this approach is that these global features cannot capture all parts of the image having different characteristics. Therefore, local computation of image information is necessary. By using salient points to represent local information, more discriminative features can be computed. In this paper we compare a wavelet-based salient point extraction algorithm with two corner detectors usingt he criteria: repeatability rate and information content. We also show that extractingc olor and texture information in the locations given by our salient points provides significantly improved results in terms of retrieval accuracy, computational complexity, and storage space of feature vectors as compared to global feature approaches.",
author = "N. Sebe and Q. Tian and E. Loupias and M. Lew and T. Huang",
year = "2002",
language = "English (US)",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "367--377",
editor = "Lew, {Michael S.} and Nicu Sebe and Eakins, {John P.}",
booktitle = "Image and Video Retrieval - International Conference, CIVR 2002, Proceedings",
address = "Germany",
note = "International Conference on Image and Video Retrieval, CIVR 2002 ; Conference date: 18-07-2002 Through 19-07-2002",
}