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EP1109132A2 Expired / Lapsed EP ⏱️ 0.0 years remaining

Method for automatic assessment of emphasis and appeal in consumer images

Assignee: Eastman Kodak Co
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Filing: 2000-12-04
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Granted: —
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Expires: 2020-12-04
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Abstract

Abstract An image is automatically assessed with respect to certain features, wherein the assessment is a determination of the degree of importance, interest or attractiveness of the image. First, a digital image is obtained corresponding to the image. Then one or more quantities are computed that are related to one or more features in the digital image, including one or more features pertaining to the content of the digital image. The quantities are processed with a reasoning algorithm that is trained on the opinions of one or more human observers, and an output is obtained from the reasoning algorithm that assesses the image. More specifically, the reasoning algorithm is a Bayesian network that provides a score which, when done for a group of images, selects one image as the emphasis image. The features pertaining to the content of the digital image include people-related features and/or subject-related features. Moreover, additional quantities may be computed that relate to objective measures of the digital image, such as colorfulness and/or sharpness.

Inventors

  • 👤 Andreas E. c/o Eastman Kodak Company Savakis
  • 👤 Stephen c/o Eastman Kodak Company Etz

Bibliographic Details

Application Number —
Jurisdiction EP
Data Source google_patents
Last Synchronized 2026-11-09 10:44
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/60; G06T7/66; G06V; G06V10/00; G06V10/40; G06V10/56; G06V40/00; G06V40/10; G06V40/16; G06V40/161; G06V40/162

Claims Analysis

Total Claims: 10
Claim 1
Independent Claim 108 words
A method for assessing an image with respect to certain features, wherein said assessment is a determination of the degree of importance, interest or attractiveness of an image, said method comprising the steps of: (a) obtaining a digital image corresponding to the image; (b) computing one or more quantities related to one or more features in the digital image, including one or more features pertaining to the content of the digital image; (c) processing said one or more quantities with a reasoning algorithm that is trained on the opinions of one or more human observers; and (d) providing an output from the reasoning algorithm that assesses the image.
Claim 2
Dependent Claim 28 words
The method as claimed in claim 1 wherein the features pertaining to the content of the digital image include at least one of people-related features and subject-related features.
Claim 3
Dependent Claim 32 words
The method as claimed in claim 1 wherein step (b) further includes computing one or more quantities related to one or more objective features pertaining to objective measures of the digital image.
Claim 4
Dependent Claim 19 words
The method as claimed in claim 3 wherein the objective features include at least one of colorfulness and sharpness.
Claim 5
Dependent Claim 27 words
The method as claimed in claim 1 wherein the reasoning algorithm in step (c) is trained at least in part from ground truth studies of candidate images.
Claim 6
Dependent Claim 15 words
The method as claimed in claim 1 wherein the reasoning algorithm is a Bayesian network.
Claim 7
Dependent Claim 24 words
The method as claimed in claim 1 wherein step (d) provides an output from the reasoning algorithm that scores the assessment of the image.
Claim 8
Dependent Claim 44 words
The method as claimed in claim 1 wherein step (a) obtains a plurality of digital images corresponding to a plurality of images and steps (b)-(d) are performed on each of the digital images such that an assessment is performed for each of the images.
Claim 9
Dependent Claim 26 words
The method as claimed in claim 8 wherein the assessments are ranked such that one image with the highest rank is selected as an emphasis image.
Claim 10
Dependent Claim 27 words
The method as claimed in claim 1 wherein the assessment of the image is used in an automatic albuming algorithm to arrange a page layout of images.

References Cited (Backward Citations)

US5424945A Cited
US5875265A Cited

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