• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.186-188
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• 2005

Hand region detection in images is an important process in many computer vision applications. It is a process that usually starts at a pixel-level, and that involves a pre-process of color space transformation followed by a classification process. A color space transformation is assumed to increase separability between skin classes for hands and non-skin classes for other parts, to increase similarity among different skin tones, and to bring a robust performance under varying illumination conditions, without any sound reasonings. In this work, we examine if the color space transformation does bring those benefits to the problem of hand region detection on a dataset of images with different hand postures, backgrounds, people, and illuminations. Results indicate that best of the color space is the normalized RGB.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.215-218
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• 2002

Gesture recognitions needed for various applications and is now gaining in importance as one method of enabling natural and intuitive human machine communication. In this paper, we propose a real time hand-signal recognition system in 3-dimensional space performs robust, real-time tracking under varying illumination. As compared with the existing method using classical pattern matching, this system is efficient with respect to speed and also presents more systematic way of defining hand-signals and developing a hand-signal recognition system. In order to verify the proposed method, we developed a virtual driving system operated by hand-signals.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.27-34
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• 2015

This paper proposes a user interface for enhancing immersiveness and usability by combining hologram and haptic device with common Leap Motion. While Leap Motion delivers physical motion of user hand to control virtual environment, it is limited to handle virtual hands on screen and interact with virtual environment in one way. In our system, hologram is coupled with Leap Motion to improve user immersiveness by arranging real and virtual hands in the same place. Moreover, we provide a interaction prototype of sense by designing a haptic device to convey touch sense in virtual environment to user's hand.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.91-96
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• 2008

증강현실(Augmented Reality)을 위한 효과적인 비전 기반 인터페이스 개발은 꾸준히 진행되어 왔으나, 대부분 환경적 제약을 받거나, 특수한 장비 혹은 복잡한 모델을 요구한다. 예를 들어, 마커를 이용하면 구현 상의 편의성과 정확성을 보장하지만, 일반적으로 마커는 환경과 대비되는 모양을 가지기 때문에, 사용자에게 거부감을 줄 수 있으며 무엇보다 복잡한 인터랙션에는 적용되기 힘들다. 한편, 손동작을 이용할 경우, 자연스럽고 다양한 인터랙션을 수행할 수 있지만, 색을 이용한 손동작 인식은 복잡한 환경에서 인식률이 크게 저하되고, 3 차원 모델 기반의 손동작 인식은 많은 연산량을 필요로 한다는 문제점을 가진다. 이로 인해 지금까지 제안된 방법을 증강현실 시스템에 적용하는 데는 한계가 있다. 본 논문에서는 기본적으로 손동작을 이용한 인터페이스를 제안하는데, 손동작 인식을 위한 알고리즘을 효율적으로 개선함으로써, 복잡한 환경에서 적은 연산량으로 자연스러운 인터랙션을 제공하고자 한다. 제안방법은 손목에 컬러 밴드를 착용하고, 색 정보를 이용하여 손을 포함하는 최소 영역을 용이하게 검출함으로써, 손 동작 인식률이 좋아지도록 하였다. 제안된 인터페이스는 손의 자연스러운 움직임을 감지해서 손의 모양과 동작에 따라서 가상의 물체를 자연스럽게 제어할 수 있도록 해 준다. 예를 들어, 손이 지정한 위치에 가상의 물체를 나타내고, 가상의 물체를 잡고 다양한 조작을 하는 등의 제어를 할 수 있다. 다양한 환경에서의 실험 및 사용자 평가를 통해 제안된 인터페이스의 유용성을 검증하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.991-995
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• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.768-775
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• 2005

For sign languages are main communication means among hearing-impaired people, there are communication difficulties between speaking-oriented people and sign-language-oriented people. Automated sign-language recognition may resolve these communication problems. In sign languages, finger spelling is used to spell names and words that are not listed in the dictionary. There have been research activities for gesture and posture recognition using glove-based devices. However, these devices are often expensive, cumbersome, and inadequate for recognizing elaborate finger spelling. Use of colored patches or gloves also cause uneasiness. In this paper, a vision-based finger spelling recognition system is introduced. In our method, captured hand region images were separated from the background using a skin detection algorithm assuming that there are no skin-colored objects in the background. Then, hand postures were recognized using a two-dimensional grid analysis method. Our recognition system is not sensitive to the size or the rotation of the input posture images. By optimizing the weights of the posture features using a genetic algorithm, our system achieved high accuracy that matches other systems using devices or colored gloves. We applied our posture recognition system for detecting Korean Sign Language, achieving better than $93\%$ accuracy.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.401-407
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• 2015

In this paper, we propose the method to eliminate EMI (Electro-Magnetic Interference) in ELF (Extremely Low Frequency) band below 2 KHz for extending the gesture-recognition distance of smart TVs to more than 3m using electric potential sensor. First, we measure the electric field generated from the back panel of a TV and propose the effective arrangement of two sets of differential sensors as well as the shielding method using metal fiber. Also, we eliminate the PLN (Power Line Noise) and other noise generated from the TV and sensors as well as surrounding environments using filters. Using the proposed EMI eliminating methods, we evaluate displacement ratio on measured signals according to distance between sensors and a moving hand. Experiment results show that our proposed method can extend the hand-gesture sensing distance using EPS (Electric Potential Sensor) up to more than 3m, which is enough to satisfy applicability of EPS based remote control to Smart TVs.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.261-262
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• 2023

거동이 불편한 사람의 경우 직접적인 제어보다 손동작으로 간접적인 제어를 함으로써 생활에 어려움이 줄고 편리한 사용이 가능하다. 사람을 인식 후 판단하고 제어가 가능할 뿐만 아니라 손동작 인식이 가능한 선풍기가 사람들에게 더 편하게 활용되고, 간단한 동작으로 제어할 수 있다. 본 논문에서는 Mediapipe를 활용하여 간단한 손동작을 바탕으로 실시간으로 풍속을 제어하고 사람을 인식하는 기능을 제공한다. 야외나 에어컨이 없는 장소의 경우 SLAM을 활용해 주행이 가능한 이동식 선풍기를 개발했다. 기존의 선풍기의 직접적인 조작 제어가 불편한 것이 누구나 쉽게 간단한 손동작을 통해 먼 거리에서의 인식을 통한 제어와 이동 기능이 기존 기능에 비해 향상됨을 기대할 수 있다.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.24-29
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• 2014

This paper proposes a kinect-based human motion recognition model for the 3D contents control after tracking the human body gesture through the camera in the infrared kinect project. The proposed human motion model in this paper computes the distance variation of the body movement from shoulder to right and left hand, wrist, arm, and elbow. The human motion model is classified into the movement directions such as the left movement, right movement, up, down, enlargement, downsizing. and selection. The proposed kinect-based human motion recognition model is very natural and low cost compared to other contact type gesture recognition technologies and device based gesture technologies with the expensive hardware system.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.1-11
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• 2017

There is a Growing Interest in Motion Recognition for Recognizing Human Motion in Camera Images. As a Result, Researches are Being Actively Conducted to Control Digital Devices with Gestures at a Long Distance. The Interface Using Gesture can be Effectively Used in the Digital Signage Industry Where the Advertisement Effect is Expected to be Exposed to the Public in Various Places. Since the Digital Signage Contents can be Easily Controlled through the Non-contact Hand Operation, it is Possible to Provide the Advertisement Information of Interest to a Large Number of People, Thereby Providing an Opportunity to Lead to Sales. Therefore, we Propose a Digital Signage Content Control System Based on Hand Movement at a Certain Distance, which can be Effectively Used for the Development of Interactive Advertizing Media.