Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. Computer Science and Artificial Intelligence Lab (CSAIL)
  3. Artificial Intelligence Lab Publications
  4. AI Memos (1959 - 2004)
  5. Structural Saliency: The Detection of Globally Salient Structures Using a Locally Connected Network

Structural Saliency: The Detection of Globally Salient Structures Using a Locally Connected Network

Thumbnail Image
Download
Name

AIM-1061.pdf

Size

1.05 MB

Format

Adobe PDF

Checksum (MD5)

e71b484e5d30850b8171e8509d10d491

Thumbnail Image
Download
Name

AIM-1061.ps

Size

2.66 MB

Format

PostScript

Checksum (MD5)

9ba82350679a18788c35c347a80742a5

Author(s)
Ullman, Shimon
•
Sha'ashua, Amnon
Date Issued
July 1, 1988
Series/Report no.
AIM-1061
Abstract
Certain salient structures in images attract our immediate attention without requiring a systematic scan. We present a method for computing saliency by a simple iterative scheme, using a uniform network of locally connected processing elements. The network uses an optimization approach to produce a "saliency map," a representation of the image emphasizing salient locations. The main properties of the network are: (i) the computations are simple and local, (ii) globally salient structures emerge with a small number of iterations, and (iii) as a by-product of the computations, contours are smoothed and gaps are filled in.
Persistent DSpace Link
http://hdl.handle.net/1721.1/6493
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.