• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.321-332
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• 1999

It is important to detect objects movement for obstacle recognition and path searching of UCT(unmanned container transporters) with vision sensor. This paper shows the method to draw out objects and to trace the trajectory of the moving object using a CCD camera and it describes the method to recognize the shape of objects by neural network. We can transform pixel points to objects position of the real space using the proposed viewport. This proposed technique is used by the single vision system based on floor map.

• 한국멀티미디어학회논문지
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• 제11권6호
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• pp.807-815
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• 2008

A simple efficient method of spotting and recognizing hand gestures in video is presented using a network of hidden Markov models and dynamic programming search algorithm. The description starts from designing a set of isolated trajectory models which are stochastic and robust enough to characterize highly variable patterns like human motion, handwriting, and speech. Those models are interconnected to form a single big network termed a spotting network or a spotter that models a continuous stream of gestures and non-gestures as well. The inference over the model is based on dynamic programming. The proposed model is highly efficient and can readily be extended to a variety of recurrent pattern recognition tasks. The test result without any engineering has shown the potential for practical application. At the end of the paper we add some related experimental result that has been obtained using a different model - dynamic Bayesian network - which is also a type of stochastic model.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권5_6호
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• pp.430-443
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• 2003

본 논문은 카메라로부터 획득된 영상 시퀀스로부터 얻어진 제스처 궤적 정보를 바탕으로 가장 기본적인 방향, 속도 및 공간 특징을 추출한 후, 각각의 특징 정보들의 인식 결과를 비교하여 어떠한 정보가 가장 유용한지 평가한다. 이를 위해 제스처 궤적 추적을 위해선 컬러 정보 및 모션 정보를 사용하였고, 인식모델로는 시간 데이타 처리에 적합한 HMM을 구성하였다. 실험을 위한 제스처 DB로는 인식하고자 하는 그래픽, 숫자, 알파벳모양의 48개 제스처에 대해 20명으로부터 5개씩 총 4800개의 데이타를 구축하였다.

• Journal of Welding and Joining
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• 제16권5호
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• pp.108-118
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• 1998

This study proposes th analysis and evaluation method of time series ultrasonic signal using the chaos feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaos time series signal analyze quantitatively weld defects. For this purpose, analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaosity resulting from distance shifts such as 0.5 and 1.0 skip distance. Such differences in chaosity enables the evaluation of unique features of defects in the weld zone. In quantitative chaos feature extraction, feature values of 4.511 and 0.091 in the case of side hole and 4.539 and 0.115 in the case of vertical hole were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaos feature extraction in this study can enhances ultrasonic pattern recognition results from defect signals of weld zone such as side hole and vertical hole.

• 제어로봇시스템학회논문지
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• 제18권4호
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• pp.328-336
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• 2012

In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

• ETRI Journal
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• 제44권2호
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• pp.286-299
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• 2022

Human activity recognition in real time is a challenging task. Recently, a plethora of studies has been proposed using deep learning architectures. The implementation of these architectures requires the high computing power of the machine and a massive database. However, handcrafted features-based machine learning models need less computing power and very accurate where features are effectively extracted. In this study, we propose a handcrafted model based on three-dimensional sequential skeleton data. The human body skeleton movement over a frame is computed through joint positions in a frame. The joints of these skeletal frames are projected into two-dimensional space, forming a "movement polygon." These polygons are further transformed into a one-dimensional space by computing amplitudes at different angles from the centroid of polygons. The feature vector is formed by the sampling of these amplitudes at different angles. The performance of the algorithm is evaluated using a support vector machine on four public datasets: MSR Action3D, Berkeley MHAD, TST Fall Detection, and NTU-RGB+D, and the highest accuracies achieved on these datasets are 94.13%, 93.34%, 95.7%, and 86.8%, respectively. These accuracies are compared with similar state-of-the-art and show superior performance.

• Journal of Welding and Joining
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• 제14권1호
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• pp.99-106
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• 1996

Development of an automatic TIG welding system incorporating a vision sensor and torch control mechanism leads to an improved welding quality and greater production efficiency. The automatic welding system should be greatly restricted in its size and weight for the LNG(Liquefied Natural Gas) storage tank and also provide a unique torch rotating mechanism which keeps the torch tip in the constant position while the angle is changed continuously to maintain the welding torch substantially perpendicular to the weld line. The developed system is driven by two translation axes X, Z and one rotational axis. A moving line window method is adopted to the image recognition of the corrugated membranes with specular reflection. This method decides original laser stripe patterns in image which is affected by multi-reflection. A self-teaching algorithm, which guides the automatic welding machine with the information provided by the CCD camera without any previous learning of a reference trajectory, was developed for tracking the corrugated membrane of the LNG tank along the weld line.

• 제어로봇시스템학회논문지
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• 제5권5호
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• pp.529-539
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• 1999

This paper suggests a new image analysis method and indoor navigation control algorithm of mobile robots using a mono vision system. In order to reduce the positional uncertainty which is generated as the robot travels around the workspace, we propose a new visual landmark recognition algorithm with 2-D graph world model which describes the workspace as only a rough plane figure. The suggested algorithm is implemented to our mobile robot and experimented in a real corridor using extended Kalman filter. The validity and performance of the proposed algorithm was verified by showing that the trajectory deviation error was maintained under 0.075m and the position estimation error was sustained under 0.05m in the resultant trajectory of the navigation.

• 전자공학회논문지CI
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• 제47권4호
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• pp.102-108
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• 2010

태양광 발전 시스템은 태양 전지에 의해 태양 에너지를 직류로 변환하며 이 직류를 인버터에 의해 일반 가정에서 사용되는 교류로 변환한다. 최근 태양광 발전 시스템의 전력량이 증가하는 추세이므로 대전력을 전송하는 3상 시스템에 관한 연구가 중요하다. 본 논문에서는 태양광전지의 계통연계 시스템의 3상 PWM 인버터의 스위치 개방이 발생했을 경우, 이를 간단히 검출하고 식별하는 방법을 제안한다. 제안 방법은 $\alpha\beta$ 평면에서 전류 벡터의 궤적 영상의 패턴을 특징으로 하여 정상상태와 각각의 고장 상태를 결정하여 트리로 분류한다. 트리 구성을 위한 고장패턴은 21개로 하였으며 고장 패턴트리의 결정을 위한 분류 파라메터는 모양, 영역, 분산각, 벡터각으로 하였다. 각 고장에 대하여 제안방법의 성능을 평가한 결과 모든 고장요소를 정확히 분류하여 패턴 트리를 구성하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권3호
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• pp.167-179
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• 2002

본 논문에서는 여러 프레임 특징으로 표현되는 분절 특징(segmental feature) 표현 방법을 제안하고, HMM 개념 위에서 음향학적 모델과 그 알고리즘을 개발하여 HMM의 약점으로 지적되는 독립관측 가정을 완화시키고자 한다. 제안된 특징 표현은 단일 프레임 특징이 음성 신호의 시간적 동적 특성 (temporal dynamics)을 제대로 표현하지 못하기 때문에, 여러 프레임을 이용하여 음성 특징을 표현하도록 한다. 분절 특징은 다항식의 회귀 함수(polynomial regression function)에 의하여 관측 벡터의 궤적으로 표현되고, 이 특징을 패턴 분류에 사용하기 위하여 음성 신호의 궤적을 효과적으로 표현하는 분절 HMM(segmental HMM)을 이용한다. SHMM은 상태에서의 관측 확률을 외적 분절 변이와 내적 분절 변이로 세분하며, 외적 분절 변이는 장기적인 변화를, 내적 분절 변이는 단기적인 변화를 나타낸다. 음향학적 모델에서 분절 특성을 고려하기 위하여 외적 분절 변이는 분절의 확률 분포로 표현하고, 내적 분절 변이는 궤적의 추정 오차로 표현하도록 SHMM을 수정한 분절 특징 HMM(SFHMM; segmental-feature HMM)을 제안한다. SFHMM에서는 분절의 관측 확률을 분절 우도와 궤적의 추정 오차의 관계로써 표현하며, 추정오차는 특정 상태에서의 분절의 우도에 대한 가중치로 고려될 수 있다. 제안된 방법의 유효성과 분절 특징의 특성을 살펴보기 위하여 TIMIT 자료를 이용하여 몇 가지 실험을 하였다. 이들 실험 결과에서, 제안된 방법이 기존의 HMM보다 매개 변수가 많더라도, 성능의 향상과 제안된 특징이 유연하고 정보를 많이 가진다는 점에서 의미가 있다고 하겠다.