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A Video Semantic Annotation System Based on User Attention Analysis

Authors:
Jin-Young Moon
Chang-Seok Bae
Wan-Chul Yoon

Keywords: video annotation; semantic analysis; user attention; human factors; video summarisation

Abstract:
Automatic semantic annotation of videos is a crucial to the success of video search and summarisation based on content semantics. In contrast to broadcast news and sports, automatic semantic annotation for non-commercial videos generated by ordinary people suffers from lack of semantic data like subtitles and webcast text. It is, however, impracticable to expect that most video shooters or owners of the non-commercial contents do semantic annotation of their videos by using annotation tools manually before video dissemination. This paper proposes a video semantic annotation system that automatically analyzes and annotates a video element with the user attention state. The attention state includes the attention target, attention degree and emotional states by using gaze and Electroencephalography data from a user watching the video. To show the benefits achieved by the proposed system, the paper describes a promising application scenario of video summarisation using semantic annotations based on user attention. The use of annotations generated by the proposed system enables the summarisation system to enrich the possible summary types.

Pages: 67 to 70

Copyright: Copyright (c) IARIA, 2012

Publication date: April 29, 2012

Published in: conference

ISSN: 2308-4448

ISBN: 978-1-61208-195-3

Location: Chamonix, France

Dates: from April 29, 2012 to May 4, 2012