• International Journal of Human Ecology
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• v.8 no.2
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• pp.47-60
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• 2007

While there is growing evidence regarding the subgroup-sensitive nature of risk factors among delinquent adolescents, researchers have paid little attention to the tracking of risks and needs by subgroups (e.g., gender, ethnicity, and the timing of onset for delinquency) among youth who are currently involved in the juvenile court system. Therefore, greater empirical attention directed toward subgroup-sensitive risk factors experienced by delinquent adolescents is thought to be both timely and necessary. A final convenience sample of 2167 court-involved adolescents in the US was used to specify subgroup-sensitive risks and needs. The results demonstrated that there were various levels of risks according to subgroups associated with gender, ethnicity, and onset for delinquency group. The findings of this study add to the extant literature on delinquency by demonstrating the importance of considering subgroups associated with gender, ethnicity, and the timing of onset for delinquency when practicing treatment or intervention programs with delinquent adolescents.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.13-16
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• 2002

This paper proposes a method to track hand gesture and to recognize the gesture pattern using Kalman filter and continuous dynamic programming (CDP). The positions of hands are predicted by Kalman filter, and corresponding pixels to the hands are extracted by skin color filter. The center of gravity of the hands is the same as the input pattern vector. The input gesture is then recognized by matching with the reference gesture patterns using CDP. From experimental results to recognize circle shape gesture and intention gestures such as “Come on” and “Bye-bye”, we show the proposed method is feasible to the hand gesture-based human -computer interaction.

• 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.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1743-1746
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• 2003

C. elegans often used to study of function of gene, but it is difficult for human observation to distinguish the mutants of C. elegans. To solve this problem, the system, which can be classified automatically using the computer vision, is studying now. In the previous works , they described the auto-tracking system and the egg-laying timing modeling, which are used to automated-classily system. In this paper, we use three kinds of features, which are related to movement , size and posture of the worm, and each feature is described mathematically and normalized. In experimental result, we validated the features for the hierarchical clustering, And we used the Calinski and Harabasz's method to find the appropriate cluster number.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.382-389
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• 2011

Salesperson Monitoring System (SMS) is geographic based information system that supports business auditing, sales area coordinating and customer management for each salesperson. Conventional SMSs focus mainly on the monitoring or logging functions, i.e., a salesperson locating or moving trail tracking. However, the schedules have been planned by human planner, and they have rarely been managed with a software system like SMS. In this paper, a mixed integer programming model for a salesperson routing schedule is provided. Then, 2-phase Genetic Algorithm (GA) is proposed to make salesperson routing schedule. Experimental results show a validity of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.549-552
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• 2006

본 논문에서는 인체의 각 구성 요소별로 추적하여 사람의 동작을 추적하는 방법을 제안한다. 입력 영상에서 피부색 등의 색상정보를 이용하여 구성요소를 검출한다. 본 논문에서는 인체의 구성요소 중 동작 추적에 가장 필요한 5가지 구성요소를 검출하여 추적하였다. 이렇게 검출된 구성요소는 개별적으로 확률전파에 의해 추적되어지고, 각 구성요소의 추적결과는 융합을 통해 전체 인체의 동작을 추적할 수 있다. 제안하는 인체동작 추적 시스템은 유아의 동작교육에 이용되는 7가지 동작에 적용되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.919-922
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• 2005

유비쿼터스 환경에서의 사용자의 위치인식 및 행동인식은 매우 중요하다. 인식을 하기위해 카메라를 쓰는 것은 센서를 이용하는 것에 비하여 여러 가지 장점들이 존재한다. 본 논문은 여러 대의 네트워크 카메라를 이용한 실내에서의 사용자의 위치인식 및 행동인식을 위한 시스템을 제안한다. 사용자의 위치인식, 행동인식을 위하여 시스템에서는 영상처리기법들이 사용된다. 또한 행동인식에서는 추가적으로 SVM을 이용한 학습 및 예측 방법이 사용된다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.437-439
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• 2011

본 논문에서는 카메라에서 입력되는 영상에서 객체의 특징 자동 추출하고 모바일 기기로 전송하여 인체의 움직임을 표현하는 시스템을 제안한다. 제안시스템은 연속된 입력영상에서 인체의 실루엣과 조인트를 자동추출하고 조인트를 추적함으로 객체를 추적한다. 추출된 특징은 객체의 각 연결점의 위치정보로 사용되며 특징을 중심으로 블록매칭 알고리즘을 적용하여 특징의 위치정보를 추적하고 모바일기기로 정보를 전송한다. 모바일 기기에서는 전송된 조인트 정보를 이용하여 인체의 움직임을 재현한다. 제안방법을 실험 동영상에 적용한 결과 인체의 실루엣과 조인트를 자동 검출하며 추출된 조인트로 인체의 매핑이 효율적으로 이루어졌다. 또한 조인트의 추적이 매핑된 인체에 반영되어 인체의 움직임도 적절히 표현되었다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.263-266
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• 2007

We introduce a vision-based hand gesture recognition fer understanding musical time and patterns without extra special devices. We suggest a simple and reliable vision-based hand gesture recognition having two features First, the motion-direction code is proposed, which is a quantized code for motion directions. Second, the conducting feature point (CFP) where the point of sudden motion changes is also proposed. The proposed hand gesture recognition system extracts the human hand region by segmenting the depth information generated by stereo matching of image sequences. And then, it follows the motion of the center of the gravity(COG) of the extracted hand region and generates the gesture features such as CFP and the direction-code finally, we obtain the current timing pattern of beat and tempo of the playing music. The experimental results on the test data set show that the musical time pattern and tempo recognition rate is over 86.42% for the motion histogram matching, and 79.75% fer the CFP tracking only.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.141-149
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• 2003

This paper proposes a method of measuring and imaging the stiffness of human soft tissue to diagnose cancers or tumors which have been difficult to detect in ultrasound B-mode imaging systems. To measure the soft tissue stiffness, sinusoidal vibrations are applied to it, and the magnitude of its mechanical vibration is determined by estimating the temporal variation of speckle pattern brightness in ultrasound B-mode images. It is verified by simulation and experiment that the proposed method can estimate the relative tissue stiffness from B-mode images with a relatively small amount of computation.