Visual content summarisation for instructional videos using AdaBoost and SIFT
by Zaynab El Khattabi; Youness Tabii; Abdelhamid Benkaddour
International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP), Vol. 6, No. 3/4, 2019

Abstract: Research contributions in video retrieval field are rising to propose solutions for automatic understanding and retrieval of video content. The aim is to make the user able to retrieve specific video sequences in a large database, based on semantic information. In this paper, we process a special case of videos, instructional videos, where text presents very rich semantic information for understanding video content. Indeed, lecture videos are the source of information used in learning systems by educators and students for archiving and sharing knowledge. However, users usually have difficulties to access accurate parts in instructional videos. In our paper, we propose a method to summarise the visual content in instructional videos. For that, first, we segment the video into shots based on SIFT. Then, key frames which are rich in text and figures are extracted from each shot based on entropy measurement. These keyframes are classified using AdaBoost to eliminate non-text frames. The text content in the lecture video summary can be detected and recognised to identify keywords for indexing and classification.

Online publication date: Mon, 02-Dec-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com