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講演・口頭発表等 - 長尾　確

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Cyber Trainground: Building-Scale Virtual Reality for Immersive Presentation Training 国際会議

Katashi Nagao, Yuto Yokoyama

IEEE Cyber Science and Technology Congress 2020 2020年8月17日 IEEE

開催年月日： 2020年8月

記述言語：英語会議種別：口頭発表（一般）

“Trainground” is a word we coined inspired by the word “playground.” It means a place for humans to perform various kinds of training and to also use machine learning to scientifically search for points they need to improve. The cyber trainground is an extension of the trainground to cyberspace. It enables training in virtual spaces that captures and reconstructs various types of information appearing in the real world, such as atmosphere and presence, to achieve an improvement effect that is the same or better than in the real world. 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.

Reading Students’ Multiple Mental States in Conversation from Facial and Heart Rate Cues 国際会議

Shimeng Peng, Shigeki Ohira, Katashi Nagao

12th International Conference on Computer Supported Education (CSEDU 2020) 2020年5月2日

開催年月日： 2020年5月

記述言語：英語会議種別：口頭発表（一般）

Students’ mental states have been widely acknowledged as crucial components for inferring their learning processes and are closely linked with learning outcomes. Understanding students’ complex mental states including concentration, confusion, frustration, and boredom in teacher-student conversation could benefit a human teacher’s perceptual and real-time decision-making capability in providing personalized and adaptive support in coaching activities. Many lines of research have explored the automatic measurement of students’ mental states in pre-designed human-computer tasks. It still remains a challenge to detect the complex mental states of students in real teacher-student conversation. In this study, we made such an attempt by describing a system for predicting the complex mental states of students from multiple perspectives: facial and physiological (heart rate) cues in real student-teacher conversation scenarios. We developed an advanced multi-sensor-based system and applied it in small-scale meetings to collect students’ multimodal conversation data. We demonstrate a multimodal analysis framework. Machine learning models were built by using extracted interpretable proxy features at a fine-grained level to validate their predictive ability regarding students’ multiple mental states. Our results provide evidence of the potential value of fusing multimodal data to understand students’ multiple mental states in real-world student-teacher conversation.

VR2ML: A Universal Recording and Machine Learning System for Improving Virtual Reality Experiences 国際会議

Yuto Yokoyama, Katashi Nagao

27th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR 2020)

開催年月日： 2020年3月

記述言語：英語会議種別：口頭発表（一般）

開催地：Atlanta 国名：アメリカ合衆国

We developed software for recording and reusing user actions and associated effects in various VR applications. In particular, we implemented two plugin systems that allow 3D motion data recorded in VR to be transferred to a machine learning module without programming. One is a system that runs on Unity and records actions and events in VR, and it is called VRec. The other is a system for using data recorded with VRec for machine learning, called VR2ML.
Currently, recording all of the movements of people and objects in VR is not possible. Since the events that occur in VR include object movements and the generation of sounds and visual effects, recording only avatar movements is not enough. The archive function provided by VR communication services is a comprehensive recording mechanism that records live performances and the like that have been done in the past in VR and allows the users to view them later. This satisfies the necessary elements for this study but is limited to recording and browsing within the same service, and the recorded data cannot be analyzed or evaluated. Therefore, a unified format is required to reuse behavioral data after VR experiences.

PSNet: A Style Transfer Network for Point Cloud Stylization on Geometry and Color 国際会議

Xu Cao, Weimin Wang, Katashi Nagao

2020 Winter Conference on Applications of Computer Vision (WACV '20)

開催年月日： 2020年3月

記述言語：英語会議種別：口頭発表（一般）

開催地：Colorado 国名：アメリカ合衆国

We propose a neural style transfer method for colored point clouds which allows stylizing the geometry and/or color property of a point cloud from another. The stylization
is achieved by manipulating the content representations and Gram-based style representations extracted from a pretrained PointNet-based classification network for colored point clouds. As Gram-based style representation is invariant to the number or the order of points, the style can also be an image in the case of stylizing the color property of a
point cloud by merely treating the image as a set of pixels.
Experimental results and analysis demonstrate the capability of the proposed method for stylizing a point cloud either from another point cloud or an image.

AI-Powered Education: Smart Learning Environment with Large Interactive Displays 招待有り国際会議

Katashi Nagao

International Display Workshops 2019

開催年月日： 2019年11月

記述言語：英語会議種別：口頭発表（一般）

国名：日本国

Our university is currently developing an advanced physical-digital learning environment that can train students to enhance their presentation and discussion skills. The environment guarantees an efficient presentation and discussion among users with state-of-the-art technologies such as touch panel digital poster panels. It includes an automatic evaluation system that efficiently records, analyses, and evaluates the presenter's presentation and discussion skills. We also have developed a digital poster authoring tool, a novel tool for creating interactive digital posters displayed on the digital poster panels. The environment also allows the students for effective self-training of presentation by authoring digital posters and getting feedbacks of automatic evaluation of presentation. We call such education promoted by the AI technologies AI-Powered Education.

Discussion-skill Analytics with Acoustic, Linguistic and Psychophysiological Data 国際会議

Katashi Nagao, Kosuke Okamoto, Shimeng Peng, Shigeki Ohira

11th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2019)

開催年月日： 2019年9月

記述言語：英語会議種別：口頭発表（一般）

開催地：Vienna 国名：オーストリア共和国

In this paper, we propose a system for improving the discussion skills of participants in a meeting by automatically evaluating statements in the meeting and effectively feeding back the results of the evaluation to them. To evaluate the skills automatically, the system uses both acoustic features and linguistic features of statements. It evaluates the way a person speaks, such as their voice size, on the basis of the acoustic features, and it also evaluates the contents of a statement, such as the consistency of context, on the basis of linguistic features. These features can be obtained from meeting minutes. Since it is difficult to evaluate the semantic contents of statements such as the consistency of context, we build a machine learning model that uses the features of minutes such as speaker attributes and the relationship of statements. In addition, we argue that participants' heart rate (HR) data can be used to effectively evaluate their cognitive performance, specifically the performance in a discussion that consists of several Q&A segments (question-and-answer pairs). We collect HR data during a discussion in real time and generate machine-learning models for evaluation. We confirmed that the proposed method is effective for evaluating the discussion skills of meeting participants.

Building-Scale Virtual Reality: Another Way to Extend Real World 国際会議

Katashi Nagao, Menglong Yang, Xu Cao, Yusuke Miyakawa

IEEE 2nd International Conference on Multimedia Information Processing and Retrieval

開催年月日： 2019年3月

記述言語：英語会議種別：口頭発表（一般）

開催地：San Jose, CA, USA 国名：アメリカ合衆国

We propose building-scale virtual reality (VR), a real-world extension method different from augmented reality (AR), that uses automatically generated indoor 3D point cloud maps. To make the entire indoor area a pose tracking area, we attach an RGB-D camera to a VR headset, collect data with it, and use deep learning to build a model learned from the data. This method is more accurate than the conventional RGB-D SLAM method. Furthermore, to modify the VR space according to the purpose, segmentation and replacement of the 3D point cloud are performed. This is hard to do in AR, but it is essential technology for VR to be used in actual real-world work. We describe a disaster simulation including virtual evacuation drills and virtual work environments as application examples.

Point Cloud Colorization Based on Densely Annotated 3D Shape Dataset 国際会議

Xu Cao, Katashi Nagao

25th International Conference on MultiMedia Modeling (MMM2019)

開催年月日： 2019年1月

記述言語：英語会議種別：口頭発表（一般）

開催地：Thessaloniki, Greece 国名：ギリシャ共和国

This paper introduces DensePoint, a densely sampled and annotated point cloud dataset containing over 10,000 single objects across 16 categories, by merging different kind of information from two existing datasets. Each point cloud in DensePoint contains 40,000 points, and each point is associated with two sorts of information: RGB value and part annotation. In addition, we propose a method for point cloud colorization by utilizing Generative Adversarial Networks (GANs). The network makes it possible to generate colours for point clouds of single objects by only giving the point cloud itself. Experiments on DensePoint show that there exist clear boundaries in point clouds between different parts of an object, suggesting that the proposed network is able to generate reasonably good colours. Our dataset is publicly available on the project page.

Automatic Evaluation of Presenters' Discussion Performance Based on their Heart Rate 国際会議

Shimeng Peng, Katashi Nagao

The 10th International Conference on Computer Supported Education (CSEDU 2018)

開催年月日： 2018年3月

記述言語：英語会議種別：口頭発表（一般）

開催地：Portugal 国名：ポルトガル共和国

Heart rate variability (HRV) has recently seen a surge in interest regarding the evaluation of cognitive performance as it always be used to measure the autonomic nervous system function. In this study, we argue that a presenters' HRV data can be used to effectively evaluate their cognitive performance, specifically presenters' performance of discussion which consists of several Q&A segments (question and answer pairs) compared with using traditional natural language processing (NLP) such as semantic analysis. To confirm this, we used a non-invasive device, i.e., Apple Watch, to collect real-time updated HR data of presenters during discussions in our lab-seminar environment, their HRV data were analyzed based on Q&A segments, and three machine-learning models were generated for evaluation: logistic regression, support vector machine, and random forest. We also discuss the meaningful HRV features (metrics). Comparative experiments were conducted involving semantic data of Q&A statements alone and a combination of HRV and semantic data. The HRV data of presenters resulted in effective evaluation of discussion performance compared with using only semantic data. The combination of these two types of data could improve the discussion performance evaluation ability to some extent.

Meeting Analytics: Creative Activity Support Based on Knowledge Discovery from Discussions 国際会議

Katashi Nagao

51st Hawaii International Conference on System Sciences

開催年月日： 2018年1月

記述言語：英語会議種別：口頭発表（一般）

開催地：Hawaii, USA 国名：アメリカ合衆国

In this paper, we present high-probability statements mentioning future tasks during meetings that should lead to innovations and facilitate creative discussions. We also propose a creative activity support system that should help users to discover and execute essential tasks.

Building Scale VR: Automatically Creating Indoor 3D Maps and its Application to Simulation of Disaster Situations 国際会議

Katashi Nagao, Yusuke Miyakawa

Future Technologies Conference (FTC) 2017

開催年月日： 2017年11月

記述言語：英語会議種別：口頭発表（一般）

開催地：Vancouver, Canada 国名：カナダ

In this paper, we explain how to implement Building-Scale VR and its applications to disaster simulations. It is useful to express disaster situations by reconstructing actual buildings into virtual space and enable users in the building to experience such situations beforehand to learn how to properly act during a disaster.

Smart Learning Environment for Discussion and Presentation Skills Training 招待有り国際会議

Katashi Nagao

2016 International Conference for Top and Emerging Computer Scientists (IC-TECS 2016)

開催年月日： 2016年12月

記述言語：英語会議種別：口頭発表（基調）

開催地：Taipei, Taiwan 国名：台湾

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 in our facility. We also have 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 some automated recognition systems that can detect interactions with the digital poster presentation system and the different discussion tools enabling a more automated skill evaluation and knowledge discovery from discussion and presentation records.

A Smart Education System for Discussion and Presentation Skills Training 招待有り国際会議

Katashi Nagao

BIT's 5th Annual World Congress of Emerging InfoTech 2016

開催年月日： 2016年11月

記述言語：英語会議種別：口頭発表（招待・特別）

開催地：Qingdao, China 国名：中華人民共和国

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 some automated recognition systems that can detect interactions with the digital poster presentation system and the different discussion tools enabling a more automated skill evaluation and knowledge discovery from discussion and presentation records.

Automatic Extraction of Task Statements from Structured Meeting Content 国際会議

Katashi Nagao, Kei Inoue, Naoya Morita and Shigeki Matsubara

7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

開催年月日： 2015年11月

記述言語：英語会議種別：口頭発表（一般）

国名：ポルトガル共和国

We previously developed a discussion mining system that records face-to-face meetings in detail, analyzes their content, and conducts knowledge discovery. Looking back on past discussion content by browsing documents, such as minutes, is an effective means for conducting future activities. In meetings at which some research topics are regularly discussed, such as seminars in laboratories, the presenters are required to discuss future issues by checking urgent matters from the discussion records. We call statements including advice or requests proposed at previous meetings "task statements" and propose a method for automatically extracting them. With this method, based on certain semantic attributes and linguistic characteristics of statements, a probabilistic model is created using the maximum entropy method. A statement is judged whether it is a task statement according to its probability. A seminar-based experiment validated the effectiveness of the proposed extraction method.

Tool and Evaluation Method for Idea Creation Support 国際会議

Ryo Takeshima, Katashi Nagao

7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

開催年月日： 2015年11月

記述言語：英語会議種別：口頭発表（一般）

国名：ポルトガル共和国

We have developed a new idea creation support tool in which (1) each idea is represented by a tree structure, (2) the idea is automatically evaluated on the basis of the tree structure so that the relative advantages among several alternative ideas is found, (3) the ideas are presented in a poster format, and (4) the ideas are shared by multiple users so that the ideas can be quoted and expanded upon by individual users. In this work, we explain the mechanisms of this tool, including the evaluation and poster conversion of ideas and collaborative idea creation, and briefly discuss our plan for the future.

A New Physical-Digital Environment for Discussion and Presentation Skills Training 国際会議

Katashi Nagao, Mehrdad Tehrani, Jovilyn B. Fajardo

The International Conference on Smart Learning Environments (ICSLE 2014)

開催年月日： 2014年7月

記述言語：英語会議種別：口頭発表（一般）

国名：中華人民共和国

Our university is currently developing an advanced physical-digital learning environment that can train the students with better discussion and presentation skills. The environment guarantees an efficient discussion among users with state-of-the-art technologies such as touch panel discussion tables and posters. It includes a data mining system that efficiently records, summarizes, and annotates the discussion. It will be further enhanced by using a vision system to facilitate the interactions enabling a more automated discussion mining.

複数コンテンツの部分関連付けに基づく論文作成支援

棚瀬達央, 大平茂輝, 長尾確

第12回情報科学技術フォーラム

内容の印象度に基づくインタラクティブな要約を用いたスライド推敲支援システム

竹島亮, 大平茂輝, 長尾確

第12回情報科学技術フォーラム

デジタルコンテンツの部分参照・引用に基づく論文作成支援

棚瀬達央, 大平茂輝, 長尾確

情報処理学会第75回全国大会

タブレットデバイスによるゼミ中のスライドへの指摘とその記録・検索手法

小林尚弥, 川西康介, 大平茂輝, 長尾確

情報処理学会第75回全国大会

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