An enhanced video summarization system using audio features for a personal video recorder

2006 ◽  
Vol 52 (1) ◽  
pp. 19-23 ◽  
Author(s):  
I. Otsuka ◽  
R. Radhakrishnan ◽  
M. Siracusa ◽  
A. Divakaran ◽  
H. Mishima
2020 ◽  
Vol 8 (6) ◽  
pp. 1683-1687

Multimedia has a significant role in communicating the information and a large amount of multimedia repositories make the browsing, retrieval and delivery of video contents. For higher education, using video as a tool for learning and teaching through multimedia application is a considerable promise. To extract the audio information from the visual content is a very challenging because it needs the extraction of high level semantic information from low level visual data. The summarization technique for videos has been proposed to improve the browsing faster for large video collections to produce more efficient content indexing and access. The proposed video summarization system for instructional videos initially separates videos into audio track and then converted into text transcript. The text transcripts are preprocessed and extracted the important relevant keywords which can be used for indexing the video file. The automatic annotation of instructional videos reduced the summary length and also preserved the semantic of the videos. The research indicates that the students found these summarized content is very helpful for preparing and reviewing the lecture material and also for the preparation during their examination.


Author(s):  
Hossam M. Zawbaa ◽  
Nashwa El-Bendary ◽  
Aboul Ella Hassanien ◽  
Ajith Abraham

Author(s):  
Hong-Mo Je ◽  
Daijin Kim ◽  
Sung-Yang Bang

In this chapter, we deal with video summarization using human facial information by face detection and recognition. Many methods of face detection and face recognition are introduced as both theoretical and practical aspects. Also, we describe the real implementation of the video summarization system based on face detection and recognition


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