• 대한인간공학회지
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• 제31권4호
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• pp.551-556
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• 2012

Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

• 대한인간공학회지
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• 제31권4호
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• pp.525-531
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• 2012

Objective: The aim of this study is to investigate learnability of gestures-commands pair when people use gestures to control a device. Background: In vision-based gesture recognition system, selecting gesture-command pairing is critical for its usability in learning. Subjective preference and its agreement score, used in previous study(Lim et al., 2012) was used to group four gesture-command pairings. To quantify the learnability, two learning models, average time model and marginal time model, were used. Method: Two sets of eight gestures, total sixteen gestures were listed by agreement score and preference data. Fourteen participants divided into two groups, memorized each set of gesture-command pair and performed gesture. For a given command, time to recall the paired gesture was collected. Results: The average recall time for initial trials were differed by preference and agreement score as well as the learning rate R driven by the two learning models. Conclusion: Preference rate agreement score showed influence on learning of gesture-command pairs. Application: This study could be applied to any device considered to adopt gesture interaction system for device control.

• 한국멀티미디어학회논문지
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• 제16권12호
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• pp.1393-1402
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• 2013

Hand gesture is one of the most popular communication methods in everyday life. In human-computer interaction applications, hand gesture recognition provides a natural way of communication between humans and computers. There are mainly two methods of hand gesture recognition: glove-based method and vision-based method. In this paper, we propose a vision-based hand gesture recognition method using Kinect. By using the depth information is efficient and robust to achieve the hand detection process. The finger labeling makes the system achieve pose classification according to the finger name and the relationship between each fingers. It also make the classification more effective and accutate. Two kinds of gesture sets can be recognized by our system. According to the experiment, the average accuracy of American Sign Language(ASL) number gesture set is 94.33%, and that of general gestures set is 95.01%. Since our system runs in real-time and has a high recognition rate, we can embed it into various applications.

• 대한인간공학회지
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• 제31권4호
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• pp.585-591
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• 2012

Objective: The aim of this study is to propose the contactless gesture-based interface on smart mobile devices for especially rhythm action games. Background: Most existing approaches about interactions of smart mobile games are tab on the touch screen. However that way is such undesirable for someone or for sometimes, because of the disabled person, or the inconvenience that users need to touch/tab specific devices. Moreover more importantly, new interaction can derive new possibilities from stranded game genre. Method: In this paper, I present a smart mobile game with contactless gesture-based interaction and the interfaces using computer vision technology. Discovering the gestures which are easy to recognize and research of interaction system that fits to game on smart mobile device are conducted as previous studies. A combination between augmented reality technique and contactless gesture interaction is also tried. Results: The rhythm game allows a user to interact with smart mobile devices using hand gestures, without touching or tabbing the screen. Moreover users can feel fun in the game as other games. Conclusion: Evaluation results show that users make low failure numbers, and the game is able to recognize gestures with quite high precision in real time. Therefore the contactless gesture-based interaction has potentials to smart mobile game. Application: The results are applied to the commercial game application.

• 대한인간공학회지
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• 제36권2호
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• pp.109-121
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• 2017

Objective: This study aims to find suitable types and styles for gesture interaction as remote control on smart TVs. Background: Smart TV is being developed rapidly in the world, and gesture interaction has a wide range of research areas, especially based on vision techniques. However, most studies are focused on the gesture recognition technology. Also, not many previous studies of gestures types and styles on smart TVs were carried out. Therefore, it is necessary to check what users prefer in terms of gesture types and styles for each operation command. Method: We conducted an experiment to extract the target user manipulation commands required for smart TVs and select the corresponding gestures. To do this, we looked at gesture styles people use for every operation command, and checked whether there are any gesture styles they prefer over others. Through these results, this study was carried out with a process selecting smart TV operation commands and gestures. Results: Eighteen TV commands have been used in this study. With agreement level as a basis, we compared the six types of gestures and five styles of gestures for each command. As for gesture type, participants generally preferred a gesture of Path-Moving type. In the case of Pan and Scroll commands, the highest agreement level (1.00) of 18 commands was shown. As for gesture styles, the participants preferred a manipulative style in 11 commands (Next, Previous, Volume up, Volume down, Play, Stop, Zoom in, Zoom out, Pan, Rotate, Scroll). Conclusion: By conducting an analysis on user-preferred gestures, nine gesture commands are proposed for gesture control on smart TVs. Most participants preferred Path-Moving type and Manipulative style gestures based on the actual operations. Application: The results can be applied to a more advanced form of the gestures in the 3D environment, such as a study on VR. The method used in this study will be utilized in various domains.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1034-1037
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• 2015

In recent years in the field of robotics, various methods have been developed to create an intimate relationship between people and robots. These methods include speech, vision, and biometrics recognition as well as gesture-based interaction. These recognition technologies are used in various wearable devices, smartphones and other electric devices for convenience. Among these technologies, gesture recognition is the most commonly used and appropriate technology for wearable devices. Gesture recognition can be classified as contact or noncontact gesture recognition. This paper proposes contact gesture recognition with IMU and EMG sensors by using the hidden Markov model (HMM) twice. Several simple behaviors make main gestures through the one-stage HMM. It is equal to the Hidden Markov model process, which is well known for pattern recognition. Additionally, the sequence of the main gestures, which comes from the one-stage HMM, creates some higher-order gestures through the two-stage HMM. In this way, more natural and intelligent gestures can be implemented through simple gestures. This advanced process can play a larger role in gesture recognition-based UX for many wearable and smart devices.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1908-1909
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• 2011

Hand gesture recognition has been widely used in virtual reality and HCI (Human-Computer-Interaction) system, which is challenging and interesting subject in the vision based area. The existing approaches for vision-driven interactive user interfaces resort to technologies such as head tracking, face and facial expression recognition, eye tracking and gesture recognition. The purpose of this paper is to combine the finite state machine (FSM) and the gesture recognition method, in other to control Windows Media Player, such as: play/pause, next, pervious, and volume up/down.

• 지능정보연구
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• 제17권1호
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• pp.53-69
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• 2011

로봇 자체 또는 로봇에 탑재된 콘텐츠와의 상호작용을 위해 일반적으로 영상 또는 음성 인식 기술이 사용된다. 그러나 영상 음성인식 기술은 아직까지 기술 및 환경 측면에서 해결해야 할 어려움이 존재하며, 실적용을 위해서는 사용자의 협조가 필요한 경우가 많다. 이로 인해 로봇과의 상호작용은 터치스크린 인터페이스를 중심으로 개발되고 있다. 향후 로봇 서비스의 확대 및 다양화를 위해서는 이들 영상 음성 중심의 기존 기술 외에 상호보완적으로 활용이 가능한 인터페이스 기술의 개발이 필요하다. 본 논문에서는 로봇 인터페이스 활용을 위한 가속도 센서 기반의 제스처 인식 기술의 개발에 대해 소개한다. 본 논문에서는 비교적 어려운 문제인 26개의 영문 알파벳 인식을 기준으로 성능을 평가하고 개발된 기술이 로봇에 적용된 사례를 제시하였다. 향후 가속도 센서가 포함된 다양한 장치들이 개발되고 이들이 로봇의 인터페이스로 사용될 때 현재 터치스크린 중심으로 된 로봇의 인터페이스 및 콘텐츠가 다양한 형태로 확장이 가능할 것으로 기대한다.

• 스마트미디어저널
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• 제1권2호
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• pp.40-46
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• 2012

본 논문은 비전 기반 신체 제스처 인식 결과를 입력인터페이스로 사용하는 상호작용 콘텐츠에 대해 기술한다. 제작된 콘텐츠 는 아시아의 공통문화요소인 도깨비를 소재로 사용하여 지역 문화에 친숙하게 접근할 수 있도록 하였다. 그리고 콘텐츠를 구성 하는 시나리오는 도깨비와의 결투장면에서 사용자의 제스처 인식을 통해 결투를 진행하므로 사용자는 자연스럽게 콘텐츠 시나리오에 몰입할 수 있다. 시나리오의 후반부에서는 사용자는 시간과 공간이 다른 다중의 결말을 선택할 수 있다. 신체 제스처 인식 부분에서는 키넥트(KINECT)를 통해 얻을 수 있는 각 신체 부분의 3차원좌표를 이용하여 정지동작인 포즈를 활용한다. 비전기반 3차원 인체 포즈 인식 기술은 HCI(Human-Computer Interaction)에서 인간의 제스처를 전달하기 위한 방법으로 사용된다. 특수한 환경에서 단순한 2차원 움직임 포즈만 인식할 수 있는 2차원 포즈모델 기반 인식 방법에 비해 3차원 관절을 묘사한 포즈모델은 관절각에 대한 정보와 신체 부위의 모양정보를 선행지식으로 사용할 수 있어서 좀 더 일반적인 환경에서 복잡한 3차원 포즈도 인식할 수 있다는 장점이 있다. 인간이 사용하는 제스처는 정지동작인 포즈들의 연속적인 동작을 통해 표현이 가능하므로 HMM을 이용하여 정지동작 포즈들로 구성된 제스처를 인식하였다. 본 논문에서 기술한 체험형 콘텐츠는 사용자가 부가적인 장치의 사용 없이 제스처 인식 결과를 입력인터페이스로 사용하였으며 사용자의 몸동작만으로 자연스럽게 콘텐츠를 조작할 수 있도록 해준다. 본 논문에서 기술한 체험형 콘텐츠는 평소 접하기 어려운 도깨비를 이용하여 사용자와 실시간 상호작용이 가능케 함으로써 몰입도와 재미를 향상시키고자 하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권1호
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• pp.157-157
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• 1999

Researches on the gesture recognition have become a very interesting topic in the computer vision area, Gesture recognition from visual images has a number of potential applicationssuch as HCI (Human Computer Interaction), VR(Virtual Reality), machine vision. To overcome thetechnical barriers in visual processing, conventional approaches have employed cumbersome devicessuch as datagloves or color marked gloves. In this research, we capture gesture images without usingexternal devices and generate a gesture trajectery composed of point-tokens. The trajectory Is spottedusing phase-based velocity constraints and recognized using the discrete left-right HMM. Inputvectors to the HMM are obtained by using the LBG clustering algorithm on a polar-coordinate spacewhere point-tokens on the Cartesian space .are converted. A gesture vocabulary is composed oftwenty-two dynamic hand gestures for editing drawing elements. In our experiment, one hundred dataper gesture are collected from twenty persons, Fifty data are used for training and another fifty datafor recognition experiment. The recognition result shows about 95% recognition rate and also thepossibility that these results can be applied to several potential systems operated by gestures. Thedeveloped system is running in real time for editing basic graphic primitives in the hardwareenvironments of a Pentium-pro (200 MHz), a Matrox Meteor graphic board and a CCD camera, anda Window95 and Visual C++ software environment.