We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Means filter, which build upon the presence of similar - rather than dissimilar - patches. Moreover, our approach extends to contextual information the local self-dissimilarity notion embedded in established detectors of corner-like interest points, thereby achieving enhanced repeatability, distinctiveness and localization accuracy.

Tombari, F., Di Stefano, L. (2015). Interest Points via Maximal Self-Dissimilarities. Springer International Publishing [10.1007/978-3-319-16808-1_39].

Interest Points via Maximal Self-Dissimilarities

TOMBARI, FEDERICO;DI STEFANO, LUIGI
2015

Abstract

We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Means filter, which build upon the presence of similar - rather than dissimilar - patches. Moreover, our approach extends to contextual information the local self-dissimilarity notion embedded in established detectors of corner-like interest points, thereby achieving enhanced repeatability, distinctiveness and localization accuracy.
2015
Computer Vision -- ACCV 2014
586
600
Tombari, F., Di Stefano, L. (2015). Interest Points via Maximal Self-Dissimilarities. Springer International Publishing [10.1007/978-3-319-16808-1_39].
Tombari, Federico; Di Stefano, Luigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/519505
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