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  <title>DSpace Collection:</title>
  <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/3437" />
  <subtitle />
  <id>http://localhost:8080/xmlui/handle/123456789/3437</id>
  <updated>2026-06-23T06:33:42Z</updated>
  <dc:date>2026-06-23T06:33:42Z</dc:date>
  <entry>
    <title>A Novel Method for Movie Character Identification Based on Graph  Matching: A Survey</title>
    <link rel="alternate" href="http://localhost:8080/xmlui/handle/123456789/3438" />
    <author>
      <name>Salve, B. S.</name>
    </author>
    <author>
      <name>Shinde, S. A.</name>
    </author>
    <id>http://localhost:8080/xmlui/handle/123456789/3438</id>
    <updated>2022-08-27T08:41:27Z</updated>
    <published>2014-04-05T00:00:00Z</published>
    <summary type="text">Title: A Novel Method for Movie Character Identification Based on Graph  Matching: A Survey
Authors: Salve, B. S.; Shinde, S. A.
Abstract: Automatic face identification of character in movies received tremendous attention from both video content &#xD;
understanding and video annotation because of their application in movie industry such as video semantic analysis, video &#xD;
summarization, and personalized video retrieval.&#xD;
Character identification of movie is challenging problem due to huge variation in the appearance of each character and &#xD;
complex background, large motion, non-rigid deformation, occlusion, huge pose, expression, wearing, clothing, even makeup and &#xD;
hairstyle changes and other uncontrolled condition make the result of face detection and face tracking unreliable. &#xD;
In particular, character identification for movie used video and script. Face tracking and clustering from video and name &#xD;
of person extract from script. Many challenges for face clustering and face-name matching are present. In good situation and clean &#xD;
environment existing methods gives better result, but in a complex movie scene performance is limited because face tracking and &#xD;
clustering process generate a noise.&#xD;
In this paper we present a comparative study of three methods using textual cues like cast list, script, subtitle and closed caption &#xD;
based on local and global face-name matching</summary>
    <dc:date>2014-04-05T00:00:00Z</dc:date>
  </entry>
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