Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Using Evolution to Learn How to Perform Interest Point Detection
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
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ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Corner detectors for affine invariant salient regions: is color important?
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Minimum explanation complexity for MOD based visual concept detection
Proceedings of the international conference on Multimedia information retrieval
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Interest or salient points are typically meaningful points within an image which can be used for a wide variety of image understanding tasks. In this paper we present a novel algorithm for detecting interest points within images. The new technique is based on finding the locations in an image which exhibit local distinctiveness. We evaluate our algorithm on the Corel stock photography test set in the context of content based image retrieval from large databases and provide quantitative comparisons to the well known SIFT interest point and Harris corner detectors as a benchmark.