NDLI: Shiatsu: semantic-based hierarchical automatic tagging of videos by segmentation using cuts

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Shiatsu: semantic-based hierarchical automatic tagging of videos by segmentation using cuts

Content Provider	ACM Digital Library
Author	Patella, Marco Bartolini, Ilaria Romani, Corrado
Abstract	The recent dramatic widespread of multimedia content over the Internet and other media channels (such as television or mobile phone platforms) points the interest of media broadcasters to the topics of video retrieval and content browsing. Semantic indexing based on content is a good starting point for an effective retrieval system, since it allows an intuitive categorization of videos. However, the annotation process is usually done manually, leading to ambiguity, lack of information, and translation problems. In this paper, we propose SHIATSU, a novel technique for automatic video tagging which is based on shot boundaries detection and hierarchical annotation processes. Our shot detection module uses a simple yet efficient algorithm based on HSV histograms and edge features. The tagging module assigns semantic concepts to both shot sequences and whole videos, by exploiting visual features extracted from key frames. We present preliminary results of our technique on the Mammie platform video set by proving its effectiveness in real scenarios.
Starting Page	57
Ending Page	62
Page Count	6
File Format	PDF
ISBN	9781450301640
DOI	10.1145/1877850.1877866
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-10-29
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Shot boundary detection Semantic concepts Video tagging
Content Type	Text
Resource Type	Article

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