Shigeki Ohira

Video Scene Annotation Based on Web Social Activities

This article describes a mechanism to acquire the semantics of video content from the activities of Web communities that use a bulletin-board system and Weblog tools to discuss video scenes.

Annotation-based multimedia summarization and translation

This paper presents techniques for multimedia annotation and their application to video summarization and translation. Our tool for annotation allows users to easily create annotation including voice transcripts, video scene descriptions, and visual/auditory object descriptions. The module for voice transcription is capable of multilingual spoken language identification and recognition. A video scene description consists of semi-automatically detected keyframes of each scene in a video clip and time codes of scenes. A visual object description is created by tracking and interactive naming of people and objects in video scenes. The text data in the multimedia annotation are syntactically and semantically structured using linguistic annotation. The proposed multimedia summarization works upon a multimodal document that consists of a video, keyframes of scenes, and transcripts of the scenes. The multimedia translation automatically generates several versions of multimedia content in different languages.

Collaborative Video Scene Annotation Based on Tag Cloud

In this paper, we propose a video scene annotation method based on tag clouds. First, user comments associated with a video are collected from existing video sharing services. Next, a tag cloud is generated from these user comments. The tag cloud is displayed on the video window of the Web browser. When users click on a tag included in the tag cloud while watching the video, the tag gets associated with the time point of the video. Users can share the information on the tags that have already been clicked. We confirmed that the coverage of annotations generated by this method is higher than that of the existing methods, and users are motivated to add tags by using tag-sharing and tag-cloud methods. This method assists in establishing highly accurate advanced video applications.

Video scene retrieval using online video annotation

In this paper, we propose an efficient method for extracting scene tags from online video annotation (e.g., comments about video scenes). To evaluate this method by applying extracted information to video scene retrieval, we have developed a video scene retrieval system based on scene tags (i.e., tags associated with video scenes). We have also developed a tag selection system that enables online users to select appropriate scene tags from data created automatically from online video annotation. Furthermore, we performed experiments on tag selection and video scene retrieval. We found that scene tags extracted by using our tag selection system had better cost performance than ones created using a conventional client-side video annotation tool.

Weblog-style video annotation and syndication

In this paper, we present a method to extend the mechanisms employed for Weblogs in order to make video contents accessible to Weblog communities. We also present a mechanism that generates Weblog entries from the browsing history of the video contents. These entries help Weblog users to reach the related video contents. By extracting knowledge on the video contents from communication among members of Weblog communities and syndicating the knowledge in the form of RDF, we can use the mechanism for annotation-based applications, such as a semantic video retrieval and summarization system.

Proposed framework for gamifying research activities

There is a variety of research activities carried out every day in a research laboratory, including investigations, seminars, experiments, analysis, and writing papers, but all of this activity is steady, methodical work that does not produce immediate, visible results. For this reason, a mechanism to maintain motivation when research is not going as expected, or to help students get on track with research when they have just been assigned to a laboratory could be useful. On the other hand, for students that have just begun their research, they may not yet understand how to proceed in their research activity. In this research, we have proposed a comprehensive gamification framework for general research activity, which clearly defines the daily issues and tasks and shows results in visual form.

Task Execution Support in Research Activity using RAC System

Research activities carried out daily in research laboratories, include conducting investigations, giving seminars on progress, performing experiments, analyzing results, and writing papers, but all of these research activities involve steady, methodical work that does not produce immediate, visible results. For this reason, a mechanism to maintain motivation when research is not going well or to help students get on track with research when they have just been assigned to a laboratory could be useful. Students that have just begun their research may not yet understand how to proceed. We previously developed a research activity concierge (RAC) system, which is a platform to encompass general research activities, and applied gamification to this system to keep user motivation high. However, even with the RAC, non-research-savvy students have difficulty handling challenges and executing tasks. In this research, we focused on discussions in seminars and introduced a mechanism to support task execution in students’ research activities by implementing automatic extraction of task statements into the RAC.

Gamifying research activity support system

Various research activities are carried out every day in research laboratories, including conducting investigations, giving seminars on progress, performing experiments, analyzing results, and writing papers, but all of these activities involve steady, methodical work that does not produce immediate, visible results. For this reason, a mechanism to maintain motivation when research is not going well or to help students get on track with research when they have just been assigned to a laboratory could be useful. Students that have just begun their research may not yet understand how to proceed. In this research, we have developed a research activity concierge (RAC) system, which is a platform to encompass general research activities, and applied gamification to this system to keep motivation high. Furthermore, we investigated the effect of the RAC system on the action setting and motivation and analyzed operational logs to improve usability.

Player type classification based on activity logs in a gamified seminar setting

University laboratory seminars provide a good opportunity for a presenter and other participants to discuss academic subject matter. In our laboratory, we have integrated a gamification technique into our seminar recording system and have developed and operated a Gamified Discussion system that sustains and improves the motivation of students to actively participate in seminars and stimulates discussions by evaluating and visualizing the argumentative skills of students. However, classification of a participants type is essential to the improvement of the system and detailed analyses of motivation. Here, we report the results of clustering for player type classification using activity logs collected from the system.