Seungjun Kim - Academia.edu (original) (raw)

Papers by Seungjun Kim

IEICE Transactions on Information and Systems, 2006

In this paper, we demonstrate an immersive and interactive broadcasting production system with a ... more In this paper, we demonstrate an immersive and interactive broadcasting production system with a new haptically enhanced multimedia broadcasting chain. The system adapts Augmented Reality (AR) techniques, which merges captured videos and virtual 3D media seamlessly through multimedia streaming technology, and haptic interaction technology in near real-time. In this system, viewers at the haptic multimedia client can interact with AR broadcasting production transmitted via communication network. We demonstrate two test applications, which show that the addition of AR-and haptic-interaction to the conventional audiovisual contents can improve immersiveness and interactivity of viewers with rich contents service.

ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications, Jul 1, 2005

Symmetry, Jul 10, 2017

Wearable devices are being explored and investigated as a promising computing platform as well as... more Wearable devices are being explored and investigated as a promising computing platform as well as a source of personal big data for the post smartphone era. To deal with a series of rapidly developed wearable prototypes, a well-structured strategy is required to assess the prototypes at various development stages. In this paper, we first design and develop variants of advanced wearable user interface prototypes, including joystick-embedded, potentiometer-embedded, motion-gesture and contactless infrared user interfaces for rapidly assessing hands-on user experience of potential futuristic user interfaces. To achieve this goal systematically, we propose a conceptual test framework and present a case study of using the proposed framework in an iterative cyclic process to prototype, test, analyze, and refine the wearable user interface prototypes. We attempt to improve the usability of the user interface prototypes by integrating initial user feedback into the leading phase of the test framework. In the following phase of the test framework, we track signs of improvements through the overall results of usability assessments, task workload assessments and user experience evaluation of the prototypes. The presented comprehensive and in-depth case study demonstrates that the iterative approach employed by the test framework was effective in assessing and enhancing the prototypes, as well as gaining insights on potential applications and establishing practical guidelines for effective and usable wearable user interface development.

Lecture Notes in Computer Science, 2004

In this paper, we discuss a haptically enhanced multimedia broadcasting system. Four stages of a ... more In this paper, we discuss a haptically enhanced multimedia broadcasting system. Four stages of a proposed system are briefly analyzed: scene capture, haptic editing, data transmission, and display with haptic interaction. In order to show usefulness of the proposed system, some potential scenarios with haptic interaction are listed. These scenarios are classified into passive and active haptic interaction scenarios, which can be fully authored by scenario writers or producers. Finally, in order to show how the haptically enhanced scenario works, a typical example is demonstrated to explain specifically for a home shopping setting.

Springer eBooks, 2006

In this paper, we propose a segmentation method for an automated differential counter using image... more In this paper, we propose a segmentation method for an automated differential counter using image analysis. The segmentation here is to extract leukocytes (white blood cells) and separate its constituents, nucleus and cytoplasm, in blood smear images. For this purpose, a regionbased active contour model is used where region information is estimated using a statistical analysis. The role of the regional statistics is mainly to attract evolving contours toward the boundaries of leukocytes, avoiding problems with initialization. And contour deformation near to the boundaries is constrained by an additional regularizer. The active contour model is implemented using a level set method and validated with a leukocyte image database.

We are increasingly in situations of divided attention, subject to interruptions, and having to d... more We are increasingly in situations of divided attention, subject to interruptions, and having to deal with an abundance of information. Our cognitive load changes in these situations of divided attention, task interruption or multitasking; this is particularly true for older adults. To help mediate our finite attention resources in performing cognitive tasks, we have to be able to measure the real-time changes in the cognitive load of individuals. This paper investigates how to assess real-time cognitive load based on psycho-physiological measurements. We use two different cognitive tasks that test perceptual speed and visio-spatial cognitive processing capabilities, and build accurate models that differentiate an individual's cognitive load (low and high) for both young and older adults. Our models perform well in assessing load every second with two different time windows: 10 seconds and 60 seconds, although less accurately for older participants. Our results show that it is possible to build a realtime assessment method for cognitive load. Based on these results, we discuss how to integrate such models into deployable systems that mediate attention effectively.

Interruptions while driving can be quite dangerous, whether these are self-interruptions or exter... more Interruptions while driving can be quite dangerous, whether these are self-interruptions or external interruptions. They increase driver workload and reduce performance on the primary driving task. Being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In this paper, we collect sensor and human-annotated data from 15 drivers, including vehicle motion, traffic states, physiological responses and driver motion. We demonstrate that this data can be used to build a machine learning classifier that can determine interruptibility every second with a 94% accuracy. We present both population and individual models and discuss the features that contribute to the high performance of this system. Such a classifier can be used to build systems that mediate when drivers use technology to self-interrupt and when drivers are interrupted by technology.

Multimedia Tools and Applications, Jun 6, 2015

Your article is protected by copyright and all rights are held exclusively by Springer Science +B... more Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com".

In this paper, we discuss a haptically enhanced broadcasting system. Four stages of a proposed sy... more In this paper, we discuss a haptically enhanced broadcasting system. Four stages of a proposed system are briefly analyzed: scene capture, edit, transmission, and display with haptic interaction. In order to show usefulness of the proposed system, a potential home shopping scenario is implemented.

We have developed an integrated driving-aware system that allows us to effectively conduct drivin... more We have developed an integrated driving-aware system that allows us to effectively conduct driving user experience (UX) studies. Our system senses driver and vehicle status, analyzes the collected data, and makes a decision about what feedback to provide a driver in a single Android application. We also propose a graphical experimental authoring tool to plan driving routes and manage UX experimental factors. This research with real-world experiments should have great positive impact on further driving-related UX studies.

Human Factors and Ergonomics in Manufacturing & Service Industries, Feb 16, 2018

This study aims to explore usability issues of watch-type wearable devices and to suggest guideli... more This study aims to explore usability issues of watch-type wearable devices and to suggest guidelines for improved operation of smartwatches. To do so, we conducted a series of surveys, interviews, and task performance experiments. Thirty smartwatch users from ages 20 to 43 years were recruited. Users' experiences of smartwatches were collected via a weeklong, online-based diary study, which consisted of various tasks to be completed while smartwatches were in use. Our study assessed usability problems associated with those tasks, concurrent tasks conducted while interacting with smartwatches, pain points/discomfort that users had while interacting with their devices, and requirements/requests of the smartwatch users. During the week of tracking, participants were asked to complete the usability evaluation three times a day using usability principles we designed for the study: information display, control, learnability, interoperability, and preference. In addition, task performance tests were conducted for the tasks most frequently conducted on touch-based displays: number entry, swiping, and scrolling. Specific usability issues of smartwatches were identified and summarized for each usability principle by triangulating survey, interview, and task performance evaluation results. Based on the insights from the results of the study, we conclude by suggesting guidelines for further enhancing users' experience of future smartwatches.

StarCraft is one of the most successful real-time strategy (RTS) games and is also actively being... more StarCraft is one of the most successful real-time strategy (RTS) games and is also actively being researched by artificial intelligence (AI) communities. Since 2010, game AI researchers have hosted annual AI competition events to develop human-level RTS AIs using StarCraft. It ranks the AI bots by their winning ratio from thousands of AI vs. AI matches without human involvement. It is questionable whether successful AI bots are also competitive and preferable to human players. In this study, we invited 20 experienced players with varying expertise to evaluate skill levels, overall performance and human likeness of AI bots. Results show that human's ranking of AI bots are not identical to the current one from AI competitions. It suggests the need for developing new AI competitions that consider human factors ("humanlikeness" or "adaptation"). Also, it revealed that the expertise levels of human players have high impact on overall performance and human-likeness evaluations of AI bots. It supports the concept of dynamically adjusting AI bots to satisfy different levels of human players. The outcomes of this study will also be useful to incorporate human factors in other active video AI competitions (e.g., Angry Birds, Fighting Game, and General Game Playing).

ACM transactions on interactive intelligent systems, Jun 30, 2017

The recent profusion of sensors has given consumers and researchers the ability to collect signif... more The recent profusion of sensors has given consumers and researchers the ability to collect significant amounts of data. However, understanding sensor data can be a challenge, because it is voluminous, multi-sourced, and unintelligible. Nonetheless, intelligent systems, such as activity recognition, require pattern analysis of sensor data streams to produce compelling results; machine learning (ML) applications enable this type of analysis. However, the number of ML experts able to proficiently classify sensor data is limited, and there remains a lack of interactive, usable tools to help intermediate users perform this type of analysis. To learn which features these tools must support, we conducted interviews with intermediate users of ML and conducted two probe-based studies with a prototype ML and visual analytics system, Gimlets. Our system implements ML applications for sensor-based time-series data as a novel domain-specific prototype that integrates interactive visual analytic features into the ML pipeline. We identify future directions for usable ML systems based on sensor data that will enable intermediate users to build systems that have been prohibitively difficult.

IEEE Access, 2018

Since 2010, annual StarCraft artificial intelligence (AI) competitions have promoted the developm... more Since 2010, annual StarCraft artificial intelligence (AI) competitions have promoted the development of successful AI players for complex real-time strategy games. In these competitions, AI players are ranked based on their win ratio over thousands of head-to-head matches. Although simple and easily implemented, this evaluation scheme may less adequately help develop more human-competitive AI players. In this paper, we recruited 45 human StarCraft players at different expertise levels (expert/medium/novice) and asked them to play against the 18 top AI players selected from the five years of competitions (2011-2015). The results show that the human evaluations of AI players differ substantially from the current standard evaluation and ranking method. In fact, from a human standpoint, there has been little progress in the quality of StarCraft AI players over the years. It is even possible that AI-only tournaments can lead to AIs being created that are unacceptable competitors for humans. This paper is the first to systematically explore the human evaluation of AI players, the evolution of AI players, and the differences between human perception and tournament-based evaluations. The discoveries from this paper can support AI developers in game companies and AI tournament organizers to better incorporate the perspective of human users into their AI systems. INDEX TERMS Video game, Starcraft, game, artificial intelligence, game AI competition, human factor, human computer interaction.

Human attention is a finite resource. When interrupted while performing a task, this resource is ... more Human attention is a finite resource. When interrupted while performing a task, this resource is split between two interactive tasks. People have to decide whether the benefits from the interruptive interaction will be enough to offset the loss of attention from the ongoing task. The issue of dealing with self-interruptions and external interruptions is particularly critical in driving situations. In general, interruptions result in a time lag before users resume their primary task, increase mental workload, and thus decrease primary task performance. Therefore, being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In order to identify situations in which drivers enter either low or high cognitive load states during naturalistic driving (i.e., opportune moments for driver interruption – e.g., more interruptible states vs. less interruptible states), the authors have examined a broad range of sensor data streams to understand real-time driver/driving states (e.g., motion capture, peripheral interaction monitoring, psycho-physiological responses, etc.), and presented a model-based driver/driving assessment by using machine learning technology.

Human attention is a finite resource. When interrupted while performing a task, this resource is ... more Human attention is a finite resource. When interrupted while performing a task, this resource is split between two interactive tasks. People have to decide whether the benefits from the interruptive interaction will be enough to offset the loss of attention from the ongoing task. The issue of dealing with self-interruptions and external interruptions is particularly critical in driving situations. In general, interruptions result in a time lag before users resume their primary task, increase mental workload, and thus decrease primary task performance. Therefore, being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In order to identify situations in which drivers enter either low or high cognitive load states during naturalistic driving (i.e., opportune moments for driver interruption – e.g., more interruptible states vs. less interruptible states), the authors have examined a broad range of sensor data streams to understand real-time driver/driving states (e.g., motion capture, peripheral interaction monitoring, psycho-physiological responses, etc.), and presented a model-based driver/driving assessment by using machine learning technology.

Advances in intelligent systems and computing, Jul 7, 2016

New IT functions have greatly increased the amount of in-car information delivered to drivers. Al... more New IT functions have greatly increased the amount of in-car information delivered to drivers. Although valuable, that information can distract drivers when delivered during vehicle operation. By inferring driver state from sensor data, prior research has shown that it can accurately identify opportune moments to deliver information. Now that we know when to best deliver information, it raises the question: what information should we deliver at those interruptible moments? To answer this question, we conducted a series of surveys and interviews and compiled a list of representative in-car information items and context factors that affect the importance of these items. By combining and exploring those context factors, we identified driving situations when each of the in-car information items is highly valuable, and verified these situations through a large online survey of drivers. Lastly, we examined what technology is available for detecting these driving situations, and which situations require further advanced technologies for detection. Results from our study offer important insights for understanding the diversity of drivers’ experiences about the value of in-car information and the ability to determine situations in which this information is valuable to drivers. With these results, researchers can then build information delivery systems that can deliver information to drivers both when they are interruptible and when they find the information valuable.

IEICE Transactions on Information and Systems, 2006

Most of the traveller guidance services (TGS) are based on GPS technology and generally concerned... more Most of the traveller guidance services (TGS) are based on GPS technology and generally concerned with the position data mapping on the simplified 2D electronic map in order to provide macro level service facility such as drive direction notifications. Digital GIS based GPS entails in situ intuitive visualization. The visually enhanced TGS can improve the global and local awareness of unknown areas. In this paper, we propose a reliable new TGS system that provides 3D street as well as pinpointed destination information in two stages of its interactive services; web-based and AR-based. The web server generates a guiding path on 2D digital map and displays 3D car-driving animation along the path. And, the AR-based service is embedded so that users can interactively obtain the detailed micro-level information of a specific section in the area with their fingertips. The implementation is based on autoformation of on-line GIS data structures from the available priori. For the verification, a 5×4 road network is selected as a test area. In the service demonstration, we show the effective awareness of street environments and the usefulness of this new TGS system.

IEICE Transactions on Information and Systems, 2006

In this paper, we demonstrate an immersive and interactive broadcasting production system with a ... more In this paper, we demonstrate an immersive and interactive broadcasting production system with a new haptically enhanced multimedia broadcasting chain. The system adapts Augmented Reality (AR) techniques, which merges captured videos and virtual 3D media seamlessly through multimedia streaming technology, and haptic interaction technology in near real-time. In this system, viewers at the haptic multimedia client can interact with AR broadcasting production transmitted via communication network. We demonstrate two test applications, which show that the addition of AR-and haptic-interaction to the conventional audiovisual contents can improve immersiveness and interactivity of viewers with rich contents service.

IEICE Transactions on Information and Systems, 2006

In this paper, we demonstrate an immersive and interactive broadcasting production system with a ... more In this paper, we demonstrate an immersive and interactive broadcasting production system with a new haptically enhanced multimedia broadcasting chain. The system adapts Augmented Reality (AR) techniques, which merges captured videos and virtual 3D media seamlessly through multimedia streaming technology, and haptic interaction technology in near real-time. In this system, viewers at the haptic multimedia client can interact with AR broadcasting production transmitted via communication network. We demonstrate two test applications, which show that the addition of AR-and haptic-interaction to the conventional audiovisual contents can improve immersiveness and interactivity of viewers with rich contents service.

ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications, Jul 1, 2005

Symmetry, Jul 10, 2017

Wearable devices are being explored and investigated as a promising computing platform as well as... more Wearable devices are being explored and investigated as a promising computing platform as well as a source of personal big data for the post smartphone era. To deal with a series of rapidly developed wearable prototypes, a well-structured strategy is required to assess the prototypes at various development stages. In this paper, we first design and develop variants of advanced wearable user interface prototypes, including joystick-embedded, potentiometer-embedded, motion-gesture and contactless infrared user interfaces for rapidly assessing hands-on user experience of potential futuristic user interfaces. To achieve this goal systematically, we propose a conceptual test framework and present a case study of using the proposed framework in an iterative cyclic process to prototype, test, analyze, and refine the wearable user interface prototypes. We attempt to improve the usability of the user interface prototypes by integrating initial user feedback into the leading phase of the test framework. In the following phase of the test framework, we track signs of improvements through the overall results of usability assessments, task workload assessments and user experience evaluation of the prototypes. The presented comprehensive and in-depth case study demonstrates that the iterative approach employed by the test framework was effective in assessing and enhancing the prototypes, as well as gaining insights on potential applications and establishing practical guidelines for effective and usable wearable user interface development.

Lecture Notes in Computer Science, 2004

In this paper, we discuss a haptically enhanced multimedia broadcasting system. Four stages of a ... more In this paper, we discuss a haptically enhanced multimedia broadcasting system. Four stages of a proposed system are briefly analyzed: scene capture, haptic editing, data transmission, and display with haptic interaction. In order to show usefulness of the proposed system, some potential scenarios with haptic interaction are listed. These scenarios are classified into passive and active haptic interaction scenarios, which can be fully authored by scenario writers or producers. Finally, in order to show how the haptically enhanced scenario works, a typical example is demonstrated to explain specifically for a home shopping setting.

Springer eBooks, 2006

In this paper, we propose a segmentation method for an automated differential counter using image... more In this paper, we propose a segmentation method for an automated differential counter using image analysis. The segmentation here is to extract leukocytes (white blood cells) and separate its constituents, nucleus and cytoplasm, in blood smear images. For this purpose, a regionbased active contour model is used where region information is estimated using a statistical analysis. The role of the regional statistics is mainly to attract evolving contours toward the boundaries of leukocytes, avoiding problems with initialization. And contour deformation near to the boundaries is constrained by an additional regularizer. The active contour model is implemented using a level set method and validated with a leukocyte image database.

We are increasingly in situations of divided attention, subject to interruptions, and having to d... more We are increasingly in situations of divided attention, subject to interruptions, and having to deal with an abundance of information. Our cognitive load changes in these situations of divided attention, task interruption or multitasking; this is particularly true for older adults. To help mediate our finite attention resources in performing cognitive tasks, we have to be able to measure the real-time changes in the cognitive load of individuals. This paper investigates how to assess real-time cognitive load based on psycho-physiological measurements. We use two different cognitive tasks that test perceptual speed and visio-spatial cognitive processing capabilities, and build accurate models that differentiate an individual's cognitive load (low and high) for both young and older adults. Our models perform well in assessing load every second with two different time windows: 10 seconds and 60 seconds, although less accurately for older participants. Our results show that it is possible to build a realtime assessment method for cognitive load. Based on these results, we discuss how to integrate such models into deployable systems that mediate attention effectively.

Interruptions while driving can be quite dangerous, whether these are self-interruptions or exter... more Interruptions while driving can be quite dangerous, whether these are self-interruptions or external interruptions. They increase driver workload and reduce performance on the primary driving task. Being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In this paper, we collect sensor and human-annotated data from 15 drivers, including vehicle motion, traffic states, physiological responses and driver motion. We demonstrate that this data can be used to build a machine learning classifier that can determine interruptibility every second with a 94% accuracy. We present both population and individual models and discuss the features that contribute to the high performance of this system. Such a classifier can be used to build systems that mediate when drivers use technology to self-interrupt and when drivers are interrupted by technology.

Multimedia Tools and Applications, Jun 6, 2015

Your article is protected by copyright and all rights are held exclusively by Springer Science +B... more Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be selfarchived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com".

In this paper, we discuss a haptically enhanced broadcasting system. Four stages of a proposed sy... more In this paper, we discuss a haptically enhanced broadcasting system. Four stages of a proposed system are briefly analyzed: scene capture, edit, transmission, and display with haptic interaction. In order to show usefulness of the proposed system, a potential home shopping scenario is implemented.

We have developed an integrated driving-aware system that allows us to effectively conduct drivin... more We have developed an integrated driving-aware system that allows us to effectively conduct driving user experience (UX) studies. Our system senses driver and vehicle status, analyzes the collected data, and makes a decision about what feedback to provide a driver in a single Android application. We also propose a graphical experimental authoring tool to plan driving routes and manage UX experimental factors. This research with real-world experiments should have great positive impact on further driving-related UX studies.

Human Factors and Ergonomics in Manufacturing & Service Industries, Feb 16, 2018

This study aims to explore usability issues of watch-type wearable devices and to suggest guideli... more This study aims to explore usability issues of watch-type wearable devices and to suggest guidelines for improved operation of smartwatches. To do so, we conducted a series of surveys, interviews, and task performance experiments. Thirty smartwatch users from ages 20 to 43 years were recruited. Users' experiences of smartwatches were collected via a weeklong, online-based diary study, which consisted of various tasks to be completed while smartwatches were in use. Our study assessed usability problems associated with those tasks, concurrent tasks conducted while interacting with smartwatches, pain points/discomfort that users had while interacting with their devices, and requirements/requests of the smartwatch users. During the week of tracking, participants were asked to complete the usability evaluation three times a day using usability principles we designed for the study: information display, control, learnability, interoperability, and preference. In addition, task performance tests were conducted for the tasks most frequently conducted on touch-based displays: number entry, swiping, and scrolling. Specific usability issues of smartwatches were identified and summarized for each usability principle by triangulating survey, interview, and task performance evaluation results. Based on the insights from the results of the study, we conclude by suggesting guidelines for further enhancing users' experience of future smartwatches.

StarCraft is one of the most successful real-time strategy (RTS) games and is also actively being... more StarCraft is one of the most successful real-time strategy (RTS) games and is also actively being researched by artificial intelligence (AI) communities. Since 2010, game AI researchers have hosted annual AI competition events to develop human-level RTS AIs using StarCraft. It ranks the AI bots by their winning ratio from thousands of AI vs. AI matches without human involvement. It is questionable whether successful AI bots are also competitive and preferable to human players. In this study, we invited 20 experienced players with varying expertise to evaluate skill levels, overall performance and human likeness of AI bots. Results show that human's ranking of AI bots are not identical to the current one from AI competitions. It suggests the need for developing new AI competitions that consider human factors ("humanlikeness" or "adaptation"). Also, it revealed that the expertise levels of human players have high impact on overall performance and human-likeness evaluations of AI bots. It supports the concept of dynamically adjusting AI bots to satisfy different levels of human players. The outcomes of this study will also be useful to incorporate human factors in other active video AI competitions (e.g., Angry Birds, Fighting Game, and General Game Playing).

ACM transactions on interactive intelligent systems, Jun 30, 2017

The recent profusion of sensors has given consumers and researchers the ability to collect signif... more The recent profusion of sensors has given consumers and researchers the ability to collect significant amounts of data. However, understanding sensor data can be a challenge, because it is voluminous, multi-sourced, and unintelligible. Nonetheless, intelligent systems, such as activity recognition, require pattern analysis of sensor data streams to produce compelling results; machine learning (ML) applications enable this type of analysis. However, the number of ML experts able to proficiently classify sensor data is limited, and there remains a lack of interactive, usable tools to help intermediate users perform this type of analysis. To learn which features these tools must support, we conducted interviews with intermediate users of ML and conducted two probe-based studies with a prototype ML and visual analytics system, Gimlets. Our system implements ML applications for sensor-based time-series data as a novel domain-specific prototype that integrates interactive visual analytic features into the ML pipeline. We identify future directions for usable ML systems based on sensor data that will enable intermediate users to build systems that have been prohibitively difficult.

IEEE Access, 2018

Since 2010, annual StarCraft artificial intelligence (AI) competitions have promoted the developm... more Since 2010, annual StarCraft artificial intelligence (AI) competitions have promoted the development of successful AI players for complex real-time strategy games. In these competitions, AI players are ranked based on their win ratio over thousands of head-to-head matches. Although simple and easily implemented, this evaluation scheme may less adequately help develop more human-competitive AI players. In this paper, we recruited 45 human StarCraft players at different expertise levels (expert/medium/novice) and asked them to play against the 18 top AI players selected from the five years of competitions (2011-2015). The results show that the human evaluations of AI players differ substantially from the current standard evaluation and ranking method. In fact, from a human standpoint, there has been little progress in the quality of StarCraft AI players over the years. It is even possible that AI-only tournaments can lead to AIs being created that are unacceptable competitors for humans. This paper is the first to systematically explore the human evaluation of AI players, the evolution of AI players, and the differences between human perception and tournament-based evaluations. The discoveries from this paper can support AI developers in game companies and AI tournament organizers to better incorporate the perspective of human users into their AI systems. INDEX TERMS Video game, Starcraft, game, artificial intelligence, game AI competition, human factor, human computer interaction.

Human attention is a finite resource. When interrupted while performing a task, this resource is ... more Human attention is a finite resource. When interrupted while performing a task, this resource is split between two interactive tasks. People have to decide whether the benefits from the interruptive interaction will be enough to offset the loss of attention from the ongoing task. The issue of dealing with self-interruptions and external interruptions is particularly critical in driving situations. In general, interruptions result in a time lag before users resume their primary task, increase mental workload, and thus decrease primary task performance. Therefore, being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In order to identify situations in which drivers enter either low or high cognitive load states during naturalistic driving (i.e., opportune moments for driver interruption – e.g., more interruptible states vs. less interruptible states), the authors have examined a broad range of sensor data streams to understand real-time driver/driving states (e.g., motion capture, peripheral interaction monitoring, psycho-physiological responses, etc.), and presented a model-based driver/driving assessment by using machine learning technology.

Human attention is a finite resource. When interrupted while performing a task, this resource is ... more Human attention is a finite resource. When interrupted while performing a task, this resource is split between two interactive tasks. People have to decide whether the benefits from the interruptive interaction will be enough to offset the loss of attention from the ongoing task. The issue of dealing with self-interruptions and external interruptions is particularly critical in driving situations. In general, interruptions result in a time lag before users resume their primary task, increase mental workload, and thus decrease primary task performance. Therefore, being able to identify when a driver is interruptible is critical for building systems that can mediate these interruptions. In order to identify situations in which drivers enter either low or high cognitive load states during naturalistic driving (i.e., opportune moments for driver interruption – e.g., more interruptible states vs. less interruptible states), the authors have examined a broad range of sensor data streams to understand real-time driver/driving states (e.g., motion capture, peripheral interaction monitoring, psycho-physiological responses, etc.), and presented a model-based driver/driving assessment by using machine learning technology.

Advances in intelligent systems and computing, Jul 7, 2016

New IT functions have greatly increased the amount of in-car information delivered to drivers. Al... more New IT functions have greatly increased the amount of in-car information delivered to drivers. Although valuable, that information can distract drivers when delivered during vehicle operation. By inferring driver state from sensor data, prior research has shown that it can accurately identify opportune moments to deliver information. Now that we know when to best deliver information, it raises the question: what information should we deliver at those interruptible moments? To answer this question, we conducted a series of surveys and interviews and compiled a list of representative in-car information items and context factors that affect the importance of these items. By combining and exploring those context factors, we identified driving situations when each of the in-car information items is highly valuable, and verified these situations through a large online survey of drivers. Lastly, we examined what technology is available for detecting these driving situations, and which situations require further advanced technologies for detection. Results from our study offer important insights for understanding the diversity of drivers’ experiences about the value of in-car information and the ability to determine situations in which this information is valuable to drivers. With these results, researchers can then build information delivery systems that can deliver information to drivers both when they are interruptible and when they find the information valuable.

IEICE Transactions on Information and Systems, 2006

Most of the traveller guidance services (TGS) are based on GPS technology and generally concerned... more Most of the traveller guidance services (TGS) are based on GPS technology and generally concerned with the position data mapping on the simplified 2D electronic map in order to provide macro level service facility such as drive direction notifications. Digital GIS based GPS entails in situ intuitive visualization. The visually enhanced TGS can improve the global and local awareness of unknown areas. In this paper, we propose a reliable new TGS system that provides 3D street as well as pinpointed destination information in two stages of its interactive services; web-based and AR-based. The web server generates a guiding path on 2D digital map and displays 3D car-driving animation along the path. And, the AR-based service is embedded so that users can interactively obtain the detailed micro-level information of a specific section in the area with their fingertips. The implementation is based on autoformation of on-line GIS data structures from the available priori. For the verification, a 5×4 road network is selected as a test area. In the service demonstration, we show the effective awareness of street environments and the usefulness of this new TGS system.

IEICE Transactions on Information and Systems, 2006

In this paper, we demonstrate an immersive and interactive broadcasting production system with a ... more In this paper, we demonstrate an immersive and interactive broadcasting production system with a new haptically enhanced multimedia broadcasting chain. The system adapts Augmented Reality (AR) techniques, which merges captured videos and virtual 3D media seamlessly through multimedia streaming technology, and haptic interaction technology in near real-time. In this system, viewers at the haptic multimedia client can interact with AR broadcasting production transmitted via communication network. We demonstrate two test applications, which show that the addition of AR-and haptic-interaction to the conventional audiovisual contents can improve immersiveness and interactivity of viewers with rich contents service.