• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.499-505
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• 2012

Objective: Research on the transformation of interaction between mobile machines and users through analysis on current gesture interface technology development trend. Background: For smooth interaction between machines and users, interface technology has evolved from "command line" to "mouse", and now "touch" and "gesture recognition" have been researched and being used. In the future, the technology is destined to evolve into "multi-modal", the fusion of the visual and auditory senses and "3D multi-modal", where three dimensional virtual world and brain waves are being used. Method: Within the development of computer interface, which follows the evolution of mobile machines, actively researching gesture interface and related technologies' trend and development will be studied comprehensively. Through investigation based on gesture based information gathering techniques, they will be separated in four categories: sensor, touch, visual, and multi-modal gesture interfaces. Each category will be researched through technology trend and existing actual examples. Through this methods, the transformation of mobile machine and human interaction will be studied. Conclusion: Gesture based interface technology realizes intelligent communication skill on interaction relation ship between existing static machines and users. Thus, this technology is important element technology that will transform the interaction between a man and a machine more dynamic. Application: The result of this study may help to develop gesture interface design currently in use.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.243-253
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• 1994

Work environments have been changed with the advent of new technologies, such as computer technology. The newer technologies, the more changes in our work conditions. However, human cognitive limits can't keep up with the change of work environments. Mental workload has been an important factors in designing modem work environments such as human-computer interaction. Designing man-machine systems requires knowledge and evaluation of the human cognitive processes which control information flow workload. Futhermore, under an urgent situation, human operator may suffer the work stress, work error, and resultant deleterious work performance. To describe the work performance in the urgent work situations, with time stress and dynamic event occurence, a new concept of information density was introduced. For a series of experiments performed for this study, three independent variables(information amount system processing time, information density) were evaluated using such dependent variables as reaction time, number of error, and number of failure. The results of statistical anlysiss indicate that the amount of information effected on all of five dependent measure. Number of failure and number of secondary task score were effected by both amount of information and operational speed of system, but reaction time of secondary task were effected by both amount of information and information density.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.222-225
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• 2000

Human frequently communicate non-linguistic information with gesture. So, we must develop efficient and fast gesture recognition algorithms for more natural human-computer interaction. However, it is difficult to recognize gesture automatically because human's body is three dimensional object with very complex structure. In this paper, we suggest a method which is able to detect key frames and frame changes, and to classify image sequence into some gesture groups. Gesture is classifiable according to moving part of body. First, we detect some frames that motion areas are changed abruptly and save those frames as key frames, and then use the frames to classify sequences. We symbolize each image of classified sequence using Principal Component Analysis(PCA) and clustering algorithm since it is better to use fewer components for representation of gestures. Symbols are used as the input symbols for the Hidden Markov Model(HMM) and recognized as a gesture with probability calculation.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.91-100
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• 2014

In this paper, we categorize existing human gesture recognition technologies to camera-based, additional hardware-based and frequency-based technologies. Then we describe several representative techniques for each of them, emphasizing their strengths and weaknesses. We define important performance issues for human gesture recognition technologies and analyze recent technologies according to the performance issues. Our analyses show that camera-based technologies are easy to use and have high accuracy, but they have limitations on recognition ranges and need additional costs for their devices. Additional hardware-based technologies are not limited by recognition ranges and not affected by light or noise, but they have the disadvantage that human must wear or carry additional devices and need additional costs for their devices. Finally, frequency-based technologies are not limited by recognition ranges, and they do not need additional devices. However, they have not commercialized yet, and their accuracies can be deteriorated by other frequencies and signals.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.805-822
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• 2015

Online communities are an important source of electronic word-of-mouth (e-WOM). However, few studies have examined the use of such messages within the Middle Eastern context. This study focuses on Saudi women as members of an online beauty forum. Previous work suggested a mediating effect of gender, with women being more likely to trust word-of-mouth and follow it up with a purchase. A conceptual model with a theoretical underpinning from existing contributions in literature provides the basis of a coding framework for the message characteristics that influence members' e-WOM adoption. A total of 310 threads and 2200 messages coded into 5725 units were content analyzed to demonstrate cases where e-WOM was adopted and indicate further continuance intention with members returning to the forum. A new category of 'community bonding' was created from the content analysis given the prevalence of emotional aspects in messages. Emotion expressed in messages, often expressed in religious terms, is as influential and important as the cognitive aspects of community bonding.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.1-9
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• 2007

The purpose of this study is to develope a criterion for evaluation on game-type learning programs by the application of HCI(Human Computer Interaction) theory. And to analyze game-type learning programs for elementary students on the criterion developed in this study. The HCI theory, which deals with principles or methods for developing systems people can use conveniently and pleasantly, has been applied to overall area of program development. And it also has been widely used to evaluate learning programs. However, there have been few studies on a game-type learning program evaluation on the basis of the HCI theory. This paper shows that evaluation criteria are developed on three viewpoint bases : usefulness, usability, and affect which are as elements in HCI. And analyzes the game-type learning programs from these three points of view. The evaluation criteria developed in this study can be applied to a basis for evaluation on game-type learning programs, and the analysis will be able to be a useful guide to game programers as well as its users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6B
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• pp.674-682
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• 2011

The multi-function console system in ships has currently exposed operational difficulties due to its complex interfaces although it supports a variety of functionalities. In this paper the concept of a human computer interaction (HCI) based multi-function console system is proposed, which can support intuitive operation environments by the analysis of users' needs to shipboard systems. Expert interviews and surveys are carried out in order to obtain users' requirements. Through the survey results, the HCI based multi-function console system is conceptually designed, which is optimized to the input of multi-touch screen. It is expected that the HCI based multi-function console system can provide ship operators with easy interfaces to the console system as well as safe operation in a rough ocean environment.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.318-333
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• 2021

Smartphones are one of the most widely used mobile devices allowing users to communicate with each other. With the development of mobile apps, many companies now provide various services for their customers by studying interactive systems in the form of mobile messengers for business marketing and commercial promotion. Such interactive systems are called "chatbots." In this paper, we propose a method of avoiding the redundant responses of chatbots, according to the utterances entered by the user. In addition, the redundant patterns of chatbot responses are classified into three categories for the first time. In order to verify the proposed method, a chatbot is implemented using Telegram, an open source messenger. By comparing the proposed method with an existent method for each pattern, it is confirmed that the proposed method significantly improves the redundancy avoidance rate. Furthermore, response performance and variation analysis of the proposed method are investigated in our experiment.