Real-Time Approaches for Video-Genre-Classification using New High-Level Descriptors and a Set of Classifiers

نویسندگان

  • Ronald Glasberg
  • Sebastian Schmiedeke
  • Martin Mocigemba
  • Thomas Sikora
چکیده

In this paper we describe in detail the recent publications related to video-genre-classification and present our improved approaches for classifying video sequences in real-time as ‘cartoon’, ‘commercial’, ‘music’, ‘news’ or ‘sport’ by analyzing the content with high-level audio-visual descriptors and classification methods. Such applications have also been discussed in the context of MPEG-7 [1]. The results demonstrate identification rates of more than 90% based on a large representative collection of 100 videos gathered from free digital TV and Internet.

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تاریخ انتشار 2008