• Journal of Advanced Navigation Technology
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• v.14 no.4
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• pp.553-561
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• 2010

This paper proposed the face tracking method which can be effectively applied to the robot's vision system. The proposed algorithm tracks the facial areas after detecting the area of video motion. Movement detection of video images is done by using median filter and erosion and dilation operation as a method for removing noise, after getting the different images using two continual frames. To extract the skin color from the moving area, the color information of sample images is used. The skin color region and the background area are separated by evaluating the similarity by generating membership functions by using MIN-MAX values as fuzzy data. For the face candidate region, the eyes are detected from C channel of color space CMY, and the mouth from Q channel of color space YIQ. The face region is tracked seeking the features of the eyes and the mouth detected from knowledge-base. Experiment includes 1,500 frames of the video images from 10 subjects, 150 frames per subject. The result shows 95.7% of detection rate (the motion areas of 1,435 frames are detected) and 97.6% of good face tracking result (1,401 faces are tracked).

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.684-690
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• 2010

Digitalized Image Information is variously used like to substitute or help human's visual ability. Unmanned observation Camera is useful for the preventing disaster, risk factor and object observation but it is mostly to depend on awareness for human's vision. The purpose of this paper is to show that Unmanned Aerial Camera carries out object recognition and autonomous position tracking. when the informations about a specific object are given. For this purpose, we have to solve complicated problems like change according to object movement and variation of color and brightness information with refraction, interference and scattering of light and noise from environmental factors like weather. But, as the first step we limit the scope of this study with simplified environment in this paper. Our goal is the study and experience about object recognition and tracking via simplified environment with unmanned aerial camera. We obtained successful results of this study and experiment.

• Archives of design research
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• v.16 no.4
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• pp.197-206
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• 2003

Nowadays, the studies on interface and cognition-engineering has become issues of general interest as newly design-methods which analyze the behavior of user on products. However existing studies were mainly done with verbal-centered method which made it difficult for the designer to apply for visual realization. Moreover many mistakes and noises are taken place whenever the designer converts verbal statements and needs of user into visual factors. Therefore the designer needs to analyze visual perception on user and product as visual-centered methods. This study applies the eye tracking method as analysing-instrument and aims to develop the analysis-framework, the concrete techniques of measurement and the application for the product design. At first the nature and the process of visual perception on products are reviewed for developing analysis method. Then the technique of eye tracking and the meaning of fixation and movement are discussed to specify the concrete method. The basic experiment of product can reveal general analysis process, advantage and guideline for the application of eye tracking method. The Study is peformed through the following 4 steps ; to pre-research into product design and visual perception theory ; to identify the concrete experiment method, to measure the fixation/movement data and analyze the raw data, to convert the result of analysis to the visual framework. Finally the major findings and the limits of the study are suggested and summarized.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.713-718
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• 2003

The CONDENSATION (Conditional Density Propagation) algorithm has a robust tracking performance and suitability for real-time implementation. However, the CONDENSATION tracker has some difficulties with real-time implementation for multiple people tracking since it requires very complicated shape modeling and a large number of samples for precise tracking performance. Further, it shows a poor tracking performance in the case of close or partially occluded people. To overcome these difficulties, we present three improvements: First, we construct effective templates of people´s shapes using the SOM (Self-Organizing Map). Second, we take the discrete HMM (Hidden Markov Modeling) for an accurate dynamical model of the people´s shape transition. Third, we use the competition rule to separate close or partially occluded people effectively. Simulation results shows that the proposed CONDENSATION algorithm can achieve robust and real-time tracking in the image sequences of a crowd of people.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.4
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• pp.349-354
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• 2005

The study on computer vision is aimed on creating a system to substitute the ability of human visual sensor. Especially, moving object tracking system is becoming an important area of study. In this study, we have proposed the tracking system of single moving object based on motion estimation. The tracking system performed motion estimation using differential image, and then tracked the moving object by controlling Pan/Tilt device of camera. Proposed tracking system is devided into image acquisition and preprocessing phase, motion estimation phase and object tracking phase. As a result of experiment, motion of moving object can be estimated. The result of tracking, object was not lost and tracked correctly.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.159-160
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• 2009

특정한 물체를 추적하는 방법에는 여러 가지가 있다. 사람의 경우 시각, 청각, 촉각, 미각 등의 여러가지 방법으로 물체를 추적하고 판단할 수 있는데 한 가지 방법 보다는 두 가지, 세 가지 방법을 동시에 사용하는 것이 물체를 추적하고 판단하는데 도움이 된다. 그러나 컴퓨터는 사용할 수 있는 정보가 제한적 이다. 물체를 추적하는데 있어서 영상데이터 만을 사용할 경우 물체가 가까이 있어 화면 전체를 차지할 경우 더 이상의 물체를 판단하기 힘들어 진다. 이러한 단점을 보완하기 위해 거리 센서를 부착함으로서 이동 로봇이 물체에 일정거리를 유지하면서 이동을 할 수 있도록 구현하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.356-359
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• 2015

본 연구는 웹사이트의 효율적이고 경험 디자인(User Experience Design : UX 디자인)적 설계가 가능하도록 사용자의 시각궤적을 통해 주시빈도를 확인한다. 사용자 경험치에 따라 웹 포털 사이트를 세 가지로 분류하고 와이어프레임을 제시하여 각 사이트의 화면분할과 정보영역을 분석한다. 시선추적 장치를 통해 세 가지 와이어프레임의 시각궤적 및 주시빈도를 확인하여 시선이 머무는 히트맵을 제시한다. 이를 통해 웹사이트의 디자인 설계시 페이지나 화면에 보이는 요소들의 효율적 배치를 위한 주시영역을 살펴본다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.382-385
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• 2016

본 연구는 포털사이트의 효율적이고 경험 디자인(User Experience Design : UX 디자인)적 설계가 가능하도록 제작하기 위하여 와이어 프레임에 대한 사용자의 시각궤적과 주시빈도를 확인한다. 국내 주요 포털 사이트를 점유비율에 따라 세 가지를 제시하고 로고의 유무에 따른 와이어 프레임을 제작하여 각 사이트의 화면분할과 정보영역을 분석한다. 시선추적 장치를 통해 총 6가지 와이어 프레임의 시각궤적 및 주시빈도를 확인하여 시선이 머무는 히트맵을 제시한다. 이를 통해 웹사이트의 디자인 설계시 페이지나 화면에 보이는 요소들의 효율적 배치를 위한 주시영역을 살펴본다.

• Korean Journal of Cognitive Science
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• v.8 no.4
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• pp.35-53
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• 1997

본 논문은 컴퓨터 시각을 이용하여 제스처를 인식함으로써 사용자에게 보다 편리한 인터페이스를 제공하는 것을 목표로 한다. 제안하는 제스처 인식 방법은 손영역을 획득하는 손영역 획득 모듈？손영역을 인식하는 인식 모듈로 나누어 수행한다. 손영역 획득 모듈에서는 손색상 모델？손색상 결정함수를 정의하여 칼라영상의 영역 분리를 수행하였고, 칼만필터를 이용하여 손색상 모델을 갱신하고 탐색영역을 제한하여 영역 추적을 용이하게 하였다. 영역 추적은 전 시점의 손영역 정보를 이용하여 현 시점의 손영역을 획득한다. 인식 모듈에서는 정적인 제스처를 표현하는 객체 프레임？행동 프레임, 그리고 동적인 제스처를 표현하는 스키마를 정의한다. 그리고 획득된 손영역？정합을 수행함으로써 제스처를 인식한다. 실험 결갬灌？제안하는 제스처 기반 인터페이스를 적용한 삼목(Tic-Tac-Toe) 게임 프로그램을 구현하였다. 사용자는 제스처를 이용하여 컴퓨터와 게임을 진행한다. 제안하는 시스템은 다른 종류의 게임 프로그램이나 마우스의 역할을 수행하는 윈도우 시스템의 제어, 그리고 가상 현실 시스템에 적용될 수 있다.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.175-182
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• 1998

An advanced visual tracking and stable grasping algorithm for a moving object is proposed. The stable grasping points for a moving 2D polygonal object are obtained through the visual tracking system with the Kalman filter and image prediction technique. The accuracy and efficiency are improved more than any other prediction algorithms for the tracking of an object. In the processing of a visual tracking. the shape predictors construct the parameterized family and grasp planner find the grasping points of unknown object through the geometric properties of the parameterized family. This algorithm conducts a process of ‘stable grasping and real time tracking’.