Paper Info
Title
A novel approach to automatic detection of presentation slides in educational videos.
Abstract
Recent advancement in learning and teaching methodology experimented with virtual reality (VR)-based presentation form to create immersive learning and training environment. The quality of such educational VR applications not only relies on the virtual model, but the 2D presentation materials such as text, diagrams and figures. However, manual designing or seeking these educational resources is both labor intensive and time-consuming. In this paper, we introduce a new automatic algorithm to detect and extract presentation slides in educational videos, which will provide abundant resources for creating slide-based immersive presentation environment. The proposed approach mainly involves five core components: shot boundary detection, training instances collection, shot classification, slide region detection and slide transition detection. We conducted comparison experiment to evaluate the performance of the proposed method. The results indicate that, in comparison with peer method, the proposed method improves the precision of slide detection from 81.6 to 92.6% and recall from 74.7 to 86.3% on average. With the detected slides, content analyzer can be employed to further extract reusable elements, which can be used for developing VR-based educational applications.
Year
DOI
Venue
2018
10.1007/s00521-017-3276-1
Neural Computing and Applications
Keywords
Field
DocType
Lecture videos, Slide detection, Video segmentation, Visual navigation system
Virtual model,Educational resources,Virtual reality,Boundary detection,Human–computer interaction,Artificial intelligence,Teaching method,Immersion (virtual reality),Region detection,Mathematics,Machine learning,Immersive learning
Journal
Volume
Issue
ISSN
29
5
0941-0643
Citations 
PageRank 
References 
1
0.36
26
Authors
5
Name
Order
Citations
PageRank
Baoquan Zhao153.16
Shujin Lin2777.74
Xin Qi3396.26
Ruomei Wang43520.82
Xiaonan Luo569792.76