NDLI: Foveated Analysis and Selection of Visual Fixations in Natural Scenes

Content Provider	IEEE Xplore Digital Library
Author	Umesh Rajashekar van der Linde, I. Bovik, A.C. Cormack, L.K.
Copyright Year	2006
Description	Author affiliation: Center for Perceptual Syst., Texas Univ., Austin, TX, USA (Umesh Rajashekar)
Abstract	The ability to automatically detect visually interesting regions in images has practical applications in the design of active machine vision systems. Analysis of the statistics of image features at observers gaze can provide insights into the mechanisms of fixation selection in humans. Using a novel foveated analysis framework, in which features were analyzed at the spatial resolution at which they were perceived, we studied the statistics of four low-level local image features: luminance, contrast, center-surround outputs of luminance and contrast, and discovered that the image patches around human fixations had, on average, higher values of each of these features than the image patches selected at random. Center-surround contrast showed the greatest difference between human and random fixations, followed by contrast, center-surround luminance, and luminance. Using these measurements, we present a new algorithm that selects image regions as likely candidates for fixation. These regions are shown to correlate well with fixations recorded from observers.
Starting Page	453
Ending Page	456
File Size	5003690
Page Count	4
File Format	PDF
ISBN	1424404800
ISSN	15224880
DOI	10.1109/ICIP.2006.312491
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Layout Humans Image analysis Machine vision Statistical analysis Spatial resolution Visual system Image edge detection Computer vision Computational modeling Active vision
Content Type	Text
Resource Type	Article

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