Faculty Profiles - NAGAO, Katashi

Papers - NAGAO, Katashi

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VR Dance Training System Capable of Human Motion Tracking and Automatic Dance Evaluation Reviewed

Kazuhiro Esaki, Katashi Nagao

PRESENCE: Virtual and Augmented Reality Vol. 29 page： 1 - 23 2023

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：The MIT Press

In this paper, a method for 3D human body tracking using multiple cameras and an automatic evaluation method using machine learning are developed to construct a virtual reality (VR) dance self-training system for fast-moving hip-hop dance. Dancers’ movement data are input as time-series data of temporal changes in joint point positions and rotations and are categorized into instructional items that are frequently pointed out by coaches as areas for improvement in actual dance lessons. For automatic dance evaluation, contrastive learning is used to obtain better expression vectors with less data. As a result, the accuracy when using contrastive learning was 0.79, a significant improvement from 0.65 without contrastive learning. In addition, since each dance is modeled by a coach, the accuracy was slightly improved to 0.84 by using, as input, the difference between the expression vectors of the model’s and the user’s movement data. Eight subjects used the VR dance training system, and results of a questionnaire survey confirmed that the system is effective.

DOI： 10.1162/PRES_a_00383

VR Presentation Training System Using Machine Learning Techniques for Automatic Evaluation Invited Reviewed International journal

Yuto Yokoyama and Katashi Nagao

International Journal of Virtual and Augmented Reality Vol. 5 ( 1 ) 2022.1

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：IGI Global

In this paper, we build an immersive training space using building-scale VR, a technology that makes a virtual space based on an entire building existing in the real world. The space is used for presentations, allowing students to self-train. The results of a presentation are automatically evaluated by using machine learning or the like and fed back to the user. In this space, users can meet their past selves (more accurately, their avatars), so they can objectively observe their presentations and recognize weak points. We developed a mechanism for recording and reproducing activities in virtual space in detail and a mechanism for applying machine learning to activity records. With these mechanisms, a system for recording, reproducing, and automatically evaluating presentations was developed.

DOI： 10.4018/IJVAR.290044

Impact Sound Generation for Audiovisual Interaction with Real-World Movable Objects in Building-Scale Virtual Reality Reviewed International journal

Nagao Katashi, Kumon Kaho, Hattori Kodai

APPLIED SCIENCES-BASEL Vol. 11 ( 16 ) 2021.8

Authorship：Lead author Language：English Publishing type：Research paper (scientific journal) Publisher：Applied Sciences (Switzerland)

In building-scale VR, where the entire interior of a large-scale building is a virtual space that users can walk around in, it is very important to handle movable objects that actually exist in the real world and not in the virtual space. We propose a mechanism to dynamically detect such objects (that are not embedded in the virtual space) in advance, and then generate a sound when one is hit with a virtual stick. Moreover, in a large indoor virtual environment, there may be multiple users at the same time, and their presence may be perceived by hearing, as well as by sight, e.g., by hearing sounds such as footsteps. We, therefore, use a GAN deep learning generation system to generate the impact sound from any object. First, in order to visually display a real-world object in virtual space, its 3D data is generated using an RGB-D camera and saved, along with its position information. At the same time, we take the image of the object and break it down into parts, estimate its material, generate the sound, and associate the sound with that part. When a VR user hits the object virtually (e.g., hits it with a virtual stick), a sound is generated. We demonstrate that users can judge the material from the sound, thus confirming the effectiveness of the proposed method.

DOI： 10.3390/app11167546

Web of Science

Scopus

VR Training System to Help Improve Photography Skills

Hiroki Kobayashi, Katashi Nagao

APPLIED SCIENCES-BASEL Vol. 13 ( 7817 ) 2023.7

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：Applied Sciences (Switzerland)

People aspiring to enhance their photography skills face multiple challenges, such as finding subjects and understanding camera-specific parameters. To address this, we present the VR Photo Training System. This system allows users to practice photography in a virtual space and provides feedback on user-taken photos using machine-learning models. These models, trained on datasets from the virtual environment, evaluate the aesthetics, composition, and color of photos. The system also includes a feature offering composition advice, which further aids in skill development. The evaluation and recommendation functions of our system have shown sufficient accuracy, proving its effectiveness for photography training.

DOI： 10.3390/app13137817

Web of Science

Scopus

Autonomous Stair Ascending and Descending by Quadruped Wheelchairs

Atsuki Akamisaka, Katashi Nagao

2023 20TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS, UR page： 295 - 301 2023.6

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

Wheelchairs are an important means of transportation for people with disabilities. However, because wheelchairs move on wheels, it is impossible for wheelchair users to move along paths such as stairs that cannot be covered by wheels, thus imposing significant limitations on their mobility. Although some wheelchairs are now available with crawler mechanisms, they cannot handle spiral staircases, in which the length of the tread differs between the inside and outside of the staircase. This paper proposes a quadruped wheelchair that can be used on all types of stairs. The proposed quadruped wheelchair is a fusion of a quadruped robot and a wheelchair, and has the potential to achieve high mobility on both plain and uneven terrain. On the other hand, it is very complicated to carry a person on the wheelchair. In this paper, we show that a quadruped wheelchair with a person on board can ascend and descend stairs using a simulator and reinforcement learning, which is a milestone toward the realization of a quadruped wheelchair.

DOI： 10.1109/UR57808.2023.10202377

Web of Science

Scopus

Virtual Reality Campuses as New Educational Metaverses

NAGAO Katashi

IEICE Transactions on Information and Systems Vol. E106.D ( 2 ) page： 93 - 100 2023.2

Language：English Publisher：The Institute of Electronics, Information and Communication Engineers

<p>This paper focuses on the potential value and future prospects of using virtual reality (VR) technology in online education. In detailing online education and the latest VR technology, we focus on metaverse construction and artificial intelligence (AI) for educational VR use. In particular, we describe a virtual university campus in which on-demand VR lectures are conducted in virtual lecture halls, automated evaluations of student learning and training using machine learning, and the linking of multiple digital campuses.</p>

DOI： 10.1587/transinf.2022eti0001

Web of Science

Scopus

CiNii Research

Effects of a new speech support application on intensive speech therapy and changes in functional brain connectivity in patients with post-stroke aphasia

Katsuno Yuta, Ueki Yoshino, Ito Keiichi, Murakami Satona, Aoyama Kiminori, Oishi Naoya, Kan Hirohito, Matsukawa Noriyuki, Nagao Katashi, Tatsumi Hiroshi

FRONTIERS IN HUMAN NEUROSCIENCE Vol. 16 page： 870733 2022.9

Language：English Publisher：Frontiers in Human Neuroscience

Aphasia is a language disorder that occurs after a stroke and impairs listening, speaking, reading, writing, and calculation skills. Patients with post-stroke aphasia in Japan are increasing due to population aging and the advancement of medical treatment. Opportunities for adequate speech therapy in chronic stroke are limited due to time constraints. Recent studies have reported that intensive speech therapy for a short period of time or continuous speech therapy using high-tech equipment, including speech applications (apps, can improve aphasia even in the chronic stage. However, its underlying mechanism for improving language function and its effect on other cognitive functions remains unclear. In the present study, we investigated whether intensive speech therapy using a newly developed speech support app could improve aphasia and other cognitive functions in patients with chronic stroke. Furthermore, we examined whether it can alter the brain network related to language and other cortical areas. Thus, we conducted a prospective, single-comparison study to examine the effects of a new speech support app on language and cognitive functions and used resting state functional MRI (rs-fMRI) regions of interest (ROI) to ROI analysis to determine changes in the related brain network. Two patients with chronic stroke participated in this study. They used the independent speech therapy system to perform eight sets of 20 randomly presented words/time (taking approximately 20 min), for 8 consecutive weeks. Their language, higher cognitive functions including attention function, and rs-fMRI, were evaluated before and after the rehabilitation intervention using the speech support app. Both patients had improved pronunciation, daily conversational situations, and attention. The rs-fMRI analysis showed increased functional connectivity of brain regions associated with language and attention related areas. Our results show that intensive speech therapy using this speech support app can improve language and attention functions even in the chronic stage of stroke, and may be a useful tool for patients with aphasia. In the future, we will conduct longitudinal studies with larger numbers of patients, which we hope will continue the trends seen in the current study, and provide even stronger evidence for the usefulness of this new speech support app.

DOI： 10.3389/fnhum.2022.870733

Web of Science

Scopus

PubMed

Recognition of Students' Mental States in Discussion Based on Multimodal Data and its Application to Educational Support Reviewed International journal

Shimeng Peng, Katashi Nagao

IEEE Access Vol. 9 page： 1 - 16 2021.2

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：IEEE

Students will experience a complex mixture of mental states during discussion, including concentration, confusion, frustration, and boredom, which have been widely acknowledged as crucial components for revealing a student's learning states. In this study, we propose using multimodal data to design an intelligent monitoring agent that can assist teachers in effectively monitoring the multiple mental states of students during discussion. We firstly developed an advanced multi-sensor-based system and applied it in a real university's research lab to collect a multimodal “in-the-wild” teacher-student conversation dataset. Then, we derived a set of proxy features from facial, heart rate, and acoustic modalities and used them to train several supervised learning classifiers with different multimodal fusion approaches single-channellevel, feature-level, and decision-level fusion to recognize students' multiple mental states in conversations. We explored how to design multimodal analytics to augment the ability to recognize different mental states and found that fusing heart rate and acoustic modalities yields better recognize the states of concentration (AUC = 0.842) and confusion (AUC = 0.695), while fusing three modalities yield the best performance in recognizing the states of frustration (AUC = 0.737) and boredom (AUC = 0.810). Our results also explored the possibility of leveraging the advantages of the replacement capabilities between different modalities to provide human teachers with solutions for addressing the challenges with monitoring students in different real-world education environments.

DOI： 10.1109/ACCESS.2021.3054176

Using Presentation Slides and Adjacent Utterances for Post-editing of Speech Recognition Results for Meeting Recordings Reviewed International journal

Kamiya K., Kawase T., Higashinaka R., Nagao K.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12848 LNAI page： 331 - 340 2021

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In recent years, the use of automatic speech recognition (ASR) systems in meetings has been increasing, such as for minutes generation and speaker diarization. The problem is that ASR systems often misrecognize words because there is domain-specific content in meetings. In this paper, we propose a novel method for automatically post-editing ASR results by using presentation slides that meeting participants use and utterances adjacent to a target utterance. We focus on automatic post-editing rather than domain adaptation because of the ease of incorporating external information, and the method can be used for arbitrary speech recognition engines. In experiments, we found that our method can significantly improve the recognition accuracy of domain-specific words (proper nouns). We also found an improvement in the word error rate (WER).

DOI： 10.1007/978-3-030-83527-9_28

Scopus

Recognition of Students' Multiple Mental States in Conversation Based on Multimodal Cues

Peng Shimeng, Ohira Shigeki, Nagao Katashi

COMPUTER SUPPORTED EDUCATION (CSEDU 2020) Vol. 1473 page： 468 - 479 2021

Language：Japanese Publisher：Communications in Computer and Information Science

Learning activities, especially face-to-face conversational coaching may invite students experience a set of learning-centered mental states including concentration, confusion, frustration, and boredom, those mental sates have been widely used as vital proxies for inferring their learning processes and are closely linked with learning outcomes. Recognizing students’ learning-centered mental states, particularly effectively detecting negative mental states such as confusion and frustration in teacher-student conversation could help teacher effectively monitor students’ learning situations in order to direct personalized and adaptive coaching resources to maximum students’ learning outcome. Most of research focused on analyzing students’ mental states using univariate modality when they completing pre-designed tasks in a computer related environment. It is still an open question on how to effectively measure students’ multiple mental states when they interacting with human teacher in coach-led conversations from various aspects. To achieve this goal, in this work, we developed an advanced multi-sensor-based system to record multi-modal conversational data of student-teacher conversations generated in a real university lab. We then attempt to derive a series of interpretable features from multiple perspectives including facial and physiological (heart rate) to characterize students’ multiple mental states. A set of supervised classifiers were built based on those features with different modality fusion methods to recognize multiple mental states of students. Our results have provided the experimental evidence to validate the outstanding predictive ability of our proposed features and the possibility of using multimodal data to recognize students’ multiple mental states in ‘in-the-wild’ student-teacher conversation.

DOI： 10.1007/978-3-030-86439-2_24

Web of Science

Scopus

Using Presentation Slides and Adjacent Utterances for Post-editing of Speech Recognition Results for Meeting Recordings

長尾確

The 24th International Conference of Text, Speech and Dialogue (TSD2021) Vol. vol. 12848 page： 331 - 340 2021

Automatic Generation of Multidestination Routes for Autonomous Wheelchairs Reviewed International journal

Yusuke Mori, Katashi Nagao

Journal of Robotics and Mechatronics Vol. 32 ( 6 ) page： 1121 - 1136 2020.12

Authorship：Last author,　Corresponding author Language：English Publishing type：Research paper (scientific journal) Publisher：Fuji Technology Press Ltd.

To solve the problem of autonomously navigating multiple destinations, which is one of the tasks in the Tsukuba Challenge 2019, this paper proposes a method for automatically generating the optimal travel route based on costs associated with routes. In the proposed method, the route information is generated by playing back the acquired driving data to perform self-localization, and the self-localization log is stored. In addition, the image group of road surfaces is acquired fromthe driving data. The costs of routes are generated based on texture analysis of the road surface image group and analysis of the self-localization log. The cost-added route information is generated by combining the costs calculated by the two methods, and by assigning the combined costs to the route. The minimum-cost multidestination route is generated by conducting a route search using cost-added route information. Then, we evaluated the proposed method by comparing it with the method of generating the route using only the distance cost. The results confirmed that the proposed method generates travel routes that account for safety when the autonomous wheelchair is being driven.

DOI： 10.20965/jrm.2020.p1121

Automatic Reconstruction of Building-Scale Indoor 3D Environment with a Deep-Reinforcement-Learning-Based Mobile Robot Reviewed

Menglong Yang, Katashi Nagao

International Journal of Robotics and Automation Technology Vol. 6 ( 1 ) page： 11-23 2019.6

Language：English Publishing type：Research paper (scientific journal)

The aim of this paper is to digitize the environments in which humans live, at low cost, and reconstruct highly accurate three-dimensional environments that are based on those in the real world. This three-dimensional content can be used such as for virtual reality environments and three-dimensional maps for automatic driving systems.
In general, however, a three-dimensional environment must be carefully reconstructed by manually moving the sensors used to first scan the real environment on which the three-dimensional one is based. This is done so that every corner of an entire area can be measured, but time and costs increase as the area expands. Therefore, a system that creates three-dimensional content that is based on real-world large-scale buildings at low cost is proposed. This involves automatically scanning the indoors with a mobile robot that uses low-cost sensors and generating 3D point clouds.
When the robot reaches an appropriate measurement position, it collects the three-dimensional data of shapes observable from that position by using a 3D sensor and 360-degree panoramic camera. The problem of determining an appropriate measurement position is called the “next best view problem," and it is difficult to solve in a complicated indoor environment. To deal with this problem, a deep reinforcement learning method is employed. It combines reinforcement learning, with which an autonomous agent learns strategies for selecting behavior, and deep learning done using a neural network. As a result, 3D point cloud data can be generated with better quality than the conventional rule-based approach.

DOI： 10.15377/2409-9694.2019.06.2

Prediction of Students' Answer Relevance in Discussion Based on their Heart Rate Data Reviewed

Shimeng Peng, Shigeki Ohira, Katashi Nagao

International Journal of Innovation and Research in Educational Sciences Vol. 6 ( 3 ) page： 414-424 2019.5

Language：English Publishing type：Research paper (scientific journal)

Whether a discussion is executed effectively depends on the completion level of the question-and-answer segments (Q&A segments) generated during the discussion. Relevance of answers could be used as a clue for evaluating the Q&A segments' completion degree. In this study, we argue that discussion participants' heart rate (HR) and its variability (HRV), which have recently received increased attention for being a crucial indicator in cognitive task performance evaluation, can be used to predict participants' answer-relevance in Q&A segments of discussions. To validate our argument, we propose an intelligent system that acquires and visualizes the HR data with the help of a non-invasive device, e.g. an Apple Watch, for measuring and recording the HR data of participants which is being updated in real-time. We also developed a web-based human-scoring method for evaluating answer-relevance of Q&A segments and question-difficulty level. A total of 17 real lab-seminar-style discussion experiments were conducted, during which the Q&A segments and the HR of participants were recorded using our proposed system. We then experimented with three machine-learning classifiers, i.e. logistic regression, support vector machine, and random forest, to predict answer-relevance of Q&A segments using the extracted HR and HRV features. Area Under the ROC Curve (AUC) was used to evaluate classifier accuracy using leave-one-student-out cross validation. We achieved an AUC= 0.76 for logistic regression classifier, an AUC=0.77 for SVM classifier, and an AUC=0.79 for random forest classifier. We examined possibilities of using participants' HR data to predict their answer-statements' relevance in Q&A segments of discussions, which provides evidence of the potential utility of the presented tools in scaling-up analysis of this type to a large number of subjects and in implementing these tools to evaluate and improve discussion outcomes in higher education environment.

Building-Scale Virtual Reality: Reconstruction and Modification of Building Interior Extends Real World Reviewed

Katashi Nagao, Menglong Yang, Yusuke Miyakawa

International Journal of Multimedia Data Engineering and Management (IJMDEM) Vol. 10 ( 1 ) page： 1-21 2019.4

Authorship：Lead author Language：English Publishing type：Research paper (scientific journal)

A method is presented that extends the real world into all buildings. This building-scale virtual reality (VR) method differs from augmented reality (AR) in that it uses automatically generated 3D point cloud maps of building interiors. It treats an entire indoor area a pose tracking area by using data collected using an RGB-D camera mounted on a VR headset and using deep learning to build a model from the data. It modifies the VR space in accordance with its intended usage by using segmentation and replacement of the 3D point clouds. This is difficult to do with AR but is essential if VR is to be used for actual real-world applications, such as disaster simulation including simulation of fires and flooding in buildings. 3D pose tracking in the building-scale VR is more accurate than conventional RGB-D simultaneous localization and mapping.

DOI： 10.4018/IJMDEM.2019010101

Picognizer：電子音の認識のためのJavaScriptライブラリの開発と評価 Reviewed

栗原一貴, 植村あい子, 板谷あかり, 北原鉄朗, 長尾確

情報処理学会論文誌 Vol. 60 ( 2 ) page： 397-410 2019.2

Language：Japanese Publishing type：Research paper (scientific journal)

われわれは今やさまざまな電子音に囲まれて生活しており、それらを検出・認識し情報処理を行うことはMaker文化の発展デジタルゲーム拡張およびゲーミフィケーションの構成のうえで有意義であるが、エンドユーザプログラマが個々の検出・認識対象について教師付き学習により認識器を構築するのは現状ではまだ容易ではない。そこで再生ごとの音響的変動が小さいという電子音の特徴を活かし、Dynamic Time Warpingなどの伝統的なテンプレートベースのパターンマッチングアルゴリズムにより電子音の検出・認識を行うJavaScriptライブラリを実装する。基礎的な性能評価を行うとともに、さまざまなユースケースを例示することでその有用性を示す。

Evidence-Based Education: Case Study of Educational Data Acquisition and Reuse

Katashi Nagao, Naoya Morita, Shigeki Ohira

Journal of Systemics, Cybernetics and Informatics Vol. 15 ( 7 ) page： 77-84 2018.2

Language：English Publishing type：Research paper (scientific journal)

There must be as many concrete indicators as possible in education, which will become signposts. People will not be confident about their learning and will become confused with tenuous instruction. It is necessary to clarify what they can do and what kinds of abilities they can improve. This paper describes a case of evidence-based education that acquires educational data from students' study activities and not only uses the data to enable instructors to check the students' levels of understanding but also improve their levels of performance. Our previous research called discussion mining was specifically used to collect various data on meetings (statements and their relationships, presentation materials such as slides, audio and video, and participants' evaluations of statements). This paper focuses on student presentations and discussions in laboratory seminars that are closely related to their research activities in writing their theses. We propose a system that supports tasks to be achieved in research activities and a machine-learning method to make the system sustainable for long-term operation by automatically extracting essential tasks. We conducted participant-based experiments that involved students and computer-simulation-based experiments to evaluate how efficiently our proposed machine-learning method updated the task extraction model. We confirmed from the participant-based experiments that informing responsible students of tasks that were automatically extracted on the system we developed improved their awareness of the tasks. Here, we also explain improvements in extraction accuracy and reductions in labeling costs with our method and how we confirmed its effectiveness through computer simulations.

Tools and evaluation methods for discussion and presentation skills training Reviewed

Katashi Nagao, Mehrdad Tehrani, Jovilyn B. Fajardo

Smart Learning Environments: a SpringerOpen Journal Vol. 2 ( 5 ) page： doi:10.1186/s40561-015-0011-1 2015.2

Authorship：Lead author Language：English Publishing type：Research paper (scientific journal)

Our university is currently developing an advanced physical-digital learning environment that can train students to enhance their discussion and presentation skills. The environment guarantees an efficient discussion among users with state-of-the-art technologies such as touch panel discussion tables, digital posters, and an interactive wall-sized whiteboard. It includes a data mining system that efficiently records, summarizes, and annotates discussions held inside our facility. We also developed a digital poster authoring tool, a novel tool for creating interactive digital posters displayed using our digital poster presentation system. Evaluation results show the efficiency of using our facilities: the data mining system and the digital poster authoring tool. In addition, our physical-digital learning environment will be further enhanced with a vision system that will detect interactions with the digital poster presentation system and the different discussion tools enabling a more automated skill evaluation and discussion mining.

DOI： doi:10.1186/s40561-015-0011-1

Support System based on Annotations of Documents and Video Scenes for Reading Technical Documents Reviewed

ISHITOYA, Kentaro, YAMAMOTO, Keisuke, OHIRA, Shigeki, NAGAO, Katashi,

Journal of the Institute of Image Information and Television Engineers Vol. 66 ( 11 ) page： J461-J470 2012.11

Language：Japanese Publishing type：Research paper (scientific journal)

Reading as many technical documents as possible is important to improve our research. When we read these documents, we can understand their contents more easily by referring to related resources such as images, audio clips, and videos. Videos contain a variety of helpful information, and facilitate our understanding of technical documents. We propose a method to define video scenes and document elements, and to annotate them with additional information such as relationships. Based on these annotations and relationships, we developed a support system that uses videos and helps readers understand technical documents. We performed some experiments to confirm whether the system was usable.

DOI： 10.3169/itej.66.J461

小型無人移動体との連携による個人用知的移動体の安全自動走行 Reviewed

渡邉賢, 長尾確

情報処理学会論文誌 Vol. 53 ( 11 ) page： 2599-2611 2012.11

A Continuous Meeting Support System Reviewed

ISHITOYA, Kentaro, OHIRA, Shigeki, NAGAO, Katashi

Transactions of Information Processing Society of Japan Vol. 53 ( 8 ) page： 2044-2048 2012.8

Language：Japanese Publishing type：Research paper (scientific journal)

In order to facilitate more efficient meetings held continuously, like project meetings, it is important to consider about past discussions and recall them in the current discussion. In this paper, we describe about a novel meeting support system consists with digital whiteboards and tablet devices which designed to be work cooperatively. With using the system, meeting results are saved as board contents which is usable to realize advanced application such as topic search or generating multi-meeting summary in content cloud server. Users are able to download contents from content cloud server and view them whenever they want with tablet device. Moreover, users are able to quote a part of past board content to the board which is using in a current meetings.

オンラインビデオアノテーションの現状と課題 Invited

長尾　確, 大平茂輝, 山本大介

映像情報メディア学会誌 Vol. 64 ( 2 ) page： 173-177 2010

ゼミコンテンツの再利用に基づく研究活動支援 Reviewed

土田貴裕, 大平茂輝, 長尾　確

情報処理学会論文誌 Vol. 51 ( 6 ) page： 1357-1370 2010

対面式会議コンテンツの作成と議論中におけるメタデータの可視化 Reviewed

土田貴裕, 大平茂輝, 長尾　確

情報処理学会論文誌 Vol. 51 ( 2 ) page： 404-416 2010

タグクラウド共有に基づく協調的映像アノテーション Reviewed

山本大介, 増田智樹, 大平茂輝, 長尾　確

人工知能学会論文誌 Vol. 25 ( 2 ) page： 243-251 2010

スライド提示型プレゼンテーション方法論の拡張手法を定量的に評価する研究 Reviewed

栗原一貴, 望月俊男, 大浦弘樹, 椿本弥生, 西森年寿, 中原淳, 山内祐平, 長尾確

情報処理学会論文誌 Vol. 51 ( 2 ) page： 391-403 2010

*Video Scene Retrieval Using Online Video Annotation Reviewed

Tomoki Masuda, Daisuke Yamamoto, Shigeki Ohira, Katashi Nagao

New Frontiers in Artificial Intelligence: JSAI2007 Conference and Workshops, Lecture Notes in Artificial Intelligence 4914, Springer-Verlag Vol. 1 ( 1 ) page： 255-268 2008.2

Video Scene Annotation Based on Web Social Activities Reviewed

YAMAMOTO, Daisuke, MASUDA, Tomoki, OHIRA, Shigeki, NAGAO, Katashi

IEEE MultiMedia Vol. 15 ( 3 ) page： 22-32 2008

Language：English Publishing type：Research paper (scientific journal)

We describe a mechanism for acquiring the semantics of video contents from the activities of Web communities that use a bulletin-board system and Weblog tools to discuss video scenes. Since these community activities include information valuable for video applications, we extract it as annotations. We developed a Web-based video sharing and annotation system called Synvie. We also performed an open experiment to acquire annotation data such as user comments on video scenes and scene-quoted Weblog entries and to evaluate our system. We have also developed a tag-based system for retrieving video scenes that is based on annotations accumulated in this open experiment.

Discussion Ontology: Knowledge Discovery from Human Activities in Meetings Reviewed

Hironori Tomobe, Katashi Nagao

New Frontiers in Artificial Intelligence: JSAI2006 Conference and Workshops, Lecture Notes in Artificial Intelligence 4384, Springer-Verlag Vol. 1 ( 1 ) page： 33-41 2007

Language：English

Discussion mining is a preliminary study on gathering knowledge based on the content of face-to-face discussion meetings. To extract knowledge from discussion content, we have to analyze not only the surface arguments, but also semantic information such as a statement's intention and the discussion flow during meetings. We require a discussion ontology for this information. This discussion ontology forms the basis of our discussion methodology and requires semantic relations between elements in meetings. We must clarify these semantic relations to build the discussion ontology. We therefore generated discussion content and analyzed meeting metadata to build the ontology.

A Video Annotation System Based on Community Activities Reviewed

YAMAMOTO, Daisuke,MASUDA, Tomoki,OHIRA, Shigeki,NAGAO, Katashi

Transactions of Information Processing Society of Japan Vol. Vol.48 ( No.12 ) 2007

Web-based Video Annotation and its Applications Reviewed

YAMAMOTO, Daisuke,NAGAO, Katashi

Transactions of the Japanese Society for Artificial Intelligence Vol. Vol.20 ( No.1 ) page： 67-75 2007

A Music Annotation System for Multiple Interpretations of Tunes Reviewed

KAJI, Katsuhiko,NAGAO, Katashi

Transactions of Information Processing Society of Japan Vol. Vol.48 ( No.1 ) page： 258-273 2007

Semantic Annotation and Transcoding: Making Web Content More Accessible Reviewed

Katashi Nagao, Yoshinari Shirai, and Kevin Squire

IEEE MultiMedia Vol. 8 ( 2 ) page： 69-81 2001

A Preferential Constraint Satisfaction Technique for Natural Language Analysis Reviewed

Katashi Nagao

IEICE Transactions on Information and Systems Vol. E77-D ( 2 ) page： 161-170 1994

A Logical Model for Plan Recognition and Belief Revision Reviewed

Katashi Nagao

IEICE Transactions on Information and Systems Vol. E77-D ( 2 ) page： 209-217 1994

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Papers - NAGAO, Katashi