Authors:
Eiji Watanabe
1
;
Takashi Ozeki
2
and
Takeshi Kohama
3
Affiliations:
1
Konan University, Japan
;
2
Fukuyama University, Japan
;
3
Kinki University, Japan
Keyword(s):
Image processing, Neural networks, Lecturer, Students, Behavior, Relation.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Digital Image Processing
;
Image and Video Analysis
;
Imaging in Computing and Business (Document Imaging, Metadata, Quality Control)
Abstract:
In this paper, we discuss the extraction of relationships between lecturer and students in lectures by using multi-layered neural networks. First, a few features concerning for behaviors by lecturer and students can be extracted based on image processing. Here, we adopt the following features as behaviors by lecturer and students; the loudness of speech by lecturer, face and hand movements by lecturer, face movements by students. Next, the relations among the above features concerning on their behaviors by lecturer and students can be represented by multi-layered neural networks. Next, we use a learning method with forgetting for neural networks for the purpose of extraction of rules. Finally, we have extracted relationships between behaviors by lecturer and students based on the internal representations in multi-layered neural networks for a real lecture.