The improbability of harris interest points

41Citations
Citations of this article
43Readers
Mendeley users who have this article in their library.
Get full text

Abstract

An elementary characterization of the map underlying Harris corners, also known as Harris interest points or key points, is provided. Two principal and basic assumptions made are: 1) Local image structure is captured in an uncommitted way, simply using weighted raw image values around every image location to describe the local image information, and 2) the lower the probability of observing the image structure present in a particular point, the more salient, or interesting, this position is, i.e., saliency is related to how uncommon it is to see a certain image structure, how surprising it is. Through the latter assumption, the axiomatization proposed makes a sound link between image saliency in computer vision on the one hand and, on the other, computational models of preattentive human visual perception, where exactly the same definition of saliency has been proposed. Because of this link, the characterization provides a compelling case in favor of Harris interest points over other approaches. © 2010 IEEE.

Cite

CITATION STYLE

APA

Loog, M., & Lauze, F. (2010). The improbability of harris interest points. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(6), 1141–1147. https://doi.org/10.1109/TPAMI.2010.53

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free