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Image region entropy: a measure of "visualness" of web images associated with one concept

Published: 06 November 2005 Publication History

Abstract

We propose a new method to measure "visualness" of concepts, that is, what extent concepts have visual characteristics. To know which concept has visually discriminative power is important for image annotation, especially automatic image annotation by image recognition system, since not all concepts are related to visual contents. Our method performs probabilistic region selection for images which are labeled as concept "X" or "non-X", and computes an entropy measure which represents "visualness" of concepts. In the experiments, we collected about forty thousand images from the World-Wide Web using the Google Image Search for 150 concepts. We examined which concepts are suitable for annotation of image contents.

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  1. Image region entropy: a measure of "visualness" of web images associated with one concept

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      cover image ACM Conferences
      MULTIMEDIA '05: Proceedings of the 13th annual ACM international conference on Multimedia
      November 2005
      1110 pages
      ISBN:1595930442
      DOI:10.1145/1101149
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

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      Published: 06 November 2005

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      Author Tags

      1. image annotation
      2. probabilistic image selection
      3. web image mining

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      MULTIMEDIA '05 Paper Acceptance Rate 49 of 312 submissions, 16%;
      Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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      • (2022)Computational Methods for Integrating Vision and LanguageundefinedOnline publication date: 8-Apr-2022
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