The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence - Special volume on computer vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Algorithms for Mining Distance-Based Outliers in Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Visual feature learning
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This paper presents an efficient method for finding salient differential features in images. We argue that the problem of finding salient features among all the possible ones is equivalent to finding outliers in a high-dimensional data set. We apply outlier detection techniques used in data mining to devise a linear time algorithm to extract the salient features. This yields a definition of saliency which rests on a more principled basis and also produces more reliable feature correspondences between images than the more conventional ones.