Masaki Onishi

Blackboard segmentation using video image of lecture and its applications

We propose a method for segmentation of written regions on a blackboard in the lecture room using a video image. We first detect the static edges of which locations on the image are stationary. Next, we extract several rectangular regions in which these static edges are located densely. Finally, by use of fuzzy rules, the extracted rectangles are merges as contextual regions, where letters and figures in each contextual region explain each context. We apply our method to automatic production of lecture video, and archives segmentation of written regions on the blackboard in lecture rooms.

Learning and recognizing behavioral patterns using position and posture of human

In general, it is possible to find certain behavioral patterns in human daily activity. Such patterns are called as daily behavioral patterns. The purpose of this research is to learn and recognize behavioral patterns. In the previous methods, it is difficult to recognize in detail how a person acts in a room because the methods recognize only a sequence of existing position of human by using the information of infrared sensors or of switching on/off of electrical appliances. On the other hand, many have proposed the methods recognizing human motions from sequential images, in most of which motion models must be prepared in advance. In this paper, we propose a method for learning and recognizing motions of human without any motion models. In addition, we also propose perceptive methods of recognizing behavioral patterns by taking not only the sequence of position but also the sequence of motion into consideration. Experiments show that our approach is able to learn and recognize human behavior and confirm effectiveness of our method

Production of video images by computer controlled camera operation based on distribution of spatiotemporal mutual information

This paper defines a spatiotemporal mutual information on the pixels of a given video image on the basis of information theory (Shannons communication theory), which can be interpreted as the theoretical estimation of interested features for human being. As an application of this spatiotemporal mutual information, we propose a method of producing a vivid video image of the distance learning by using the computer controlled camera operation and switching of plural camera images on the basis of the video image processing. Results of the questionnaire survey for the video image produced by the method confirm the effectiveness of our approach.

Production of video images by computer controlled cameras and its application to TV conference system

TV conference systems have been widely used recently. A participant of each site proceeds with a TV conference using video image on a screen and voice of a partner site. In this case, a fixed video camera shoots a scene of a site in general. The video image taken by a fixed camera, however, is lacking in changes. Also the fixed camera does not take shots efficiency that the participants of a partner site pay attention. As one of the candidates to avoid these defects, there is a method that the computer-controlled cameras shoots the scene. In this paper we propose an algorithm of shooting the best shot by computer-controlled cameras. The shooting algorithm is mainly decided by estimating an area of the image with high degree of attention, which is given by not only visual information but also auditory information. By using an experimental system, we confirm the effectiveness of our approach by examining a questionnaire from the participants of TV conferences.