• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.615-618
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• 2007

본 실험을 통하여 연속된 프레임을 갖는 이미지 영상을 히스토그램의 절대값을 이용하여 영상의 모션에너지를 분석하는 방법을 제안한다. 입력되어지는 영상은 그 내용의 흐름에 따라 각각의 프레임마다 다른 모션에너지를 발생하고 모션에너지의 피크값을 검출 할 임계값과 영상의 분할을 통하여 영상내 객체의 이동방향이나 움직임의 강도 등을 파악할 수 있다. 이 모션에너지는 여러 가지로 활용할 수 있으며 실험을 통하여 차량의 주행속도를 자동으로 검출해 낼 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.325-327
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• 2006

본 논문은 모션 그래디언트 히스토그램(Motion Gradient Histogram : 이하 'MGH')을 적용하여 동영상에서 나타나는 다수 객체들의 동작 검출 및 인식을 실시간으로 구현하는 방법을 제안한다. 인식하고자 하는 대상에 대한 기본적인 템플릿 동영상들의 MGH와 일정 프레임 간격마다 동영상의 MGH를 비교하여 검출 및 인식이 이루어진다. 동시에 다수의 동작이 있는 경우 동작이 발생하는 영역을 모션 에너지 영상(Motion Energy Image : MEI) 기법으로 추출하여 해당 영역별 MGH를 구함으로써 다수 동작을 인식할 수 있도록 한다.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1075-1082
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• 2007

In this paper, we propose the method of multiple human action recognition on video clip. For being invariant to the change of speed or size of actions, Spatial-Temporal Pyramid method is applied. Proposed method can minimize the complexity of the procedures owing to select Motion Gradient Histogram (MGH) based on statistical approach for action representation feature. For multiple action detection, Motion Energy Image (MEI) of binary frame difference accumulations is adapted and then we detect each action of which area is represented by MGH. The action MGH should be compared with pre-learning MGH having pyramid method. As a result, recognition can be done by the analyze between action MGH and pre-learning MGH. Ten video clips are used for evaluating the proposed method. We have various experiments such as mono action, multiple action, speed and site scale-changes, comparison with previous method. As a result, we can see that proposed method is simple and efficient to recognize multiple human action with stale variations.

• Journal of Advanced Navigation Technology
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• v.2 no.2
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• pp.107-115
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• 1998

In this paper, we propose a robust moving object tracking(MOT) method based on motion energy and prediction. MOT consists of two steps: moving object extraction step(MOES) and moving object tracking step(MOTS). For MOES, we use improved motion energy method. For MOTS, we predict the next location of moving object based on distance and direction information among previous instances, so that we can reduce the search space for correspondence. We apply the method to both synthetic and real world sequences and find that the method works well even in the presence of occlusion and disocclusion.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.966-969
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• 2006

This paper proposed frequency that is done special quality Tuesday that can create wave length and size of RGB color by sound and method to convert to amplitude. Talk feedback of division side according to the change amount of motion energy through SAD by 4 in each frame of animation that is inputed by proposed method, and grasped stream and action of object. Also, meaning of animation through collar price that can do modelling by sound show.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.837-840
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• 2000

동영상에서 움직이는 객체 분할 및 모션 예측을 동시에 수행할 수 있는 연구는 다양한 방법으로 시도 되어 왔다. 실제 이미지를 서로 다른 움직임이나 서로 다른 공간적인 특정 영역으로 분리 될 수 있다고 가정 한다면 복수의 객체 또는 객체의 움직임으로 표현 할 수 있다. 객체 분할 측면에서 볼 때 효율적인 분할을 위해서는 특징 입력 벡터의 선택이 중요한 변수로 작용한다. 본 연구에서는 정밀한 객체 분할을 위해 밝기, 질감(Texture) 정보와 같은 정지영상의 특징 입력 벡터와 움직임 벡터 같은 동영상의 특징 입력 벡터를 동시에 사용한다. 분리된 객체는 각각의 클래스를 구성하게 되고 이를 위한 클래스 분류기로서 Median Radial Basis 신경 회로망을 사용한다. 객체 분할과 움직임 예측을 위해서 확률적 방법을 통한 에너지 함수를 구하고 비용함수를 도입한다. 신경 회로망의 각 Basis 함수는 영상의 특정한 영역에서 활성화되며 객체의 분류를 위해 신경 회로망 출력으로 가중치의 합으로서 나타나게 된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1029-1036
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• 2018

This paper is a study on the development of optimal control system for lighting and air conditioning equipment to save the energy in campus environment. In the case of controling system developed through this research, lighting and air conditioner are controlled by both information on the number of people entering and leaving the room through the motion sensor and image processing, and the information on temperature and humidity. In addition, energy saving is enabled by the results that are controlled through data integration monitoring and command execution functions according to the control signals.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.712-721
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• 2010

This paper proposes a new fire-flame detection method using probabilistic membership function of visual features and Fuzzy Finite Automata (FFA). First, moving regions are detected by analyzing the background subtraction and candidate flame regions then identified by applying flame color models. Since flame regions generally have continuous and an irregular pattern continuously, membership functions of variance of intensity, wavelet energy and motion orientation are generated and applied to FFA. Since FFA combines the capabilities of automata with fuzzy logic, it not only provides a systemic approach to handle uncertainty in computational systems, but also can handle continuous spaces. The proposed algorithm is successfully applied to various fire videos and shows a better detection performance when compared with other methods.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.109-117
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• 2004

In this paper, we propose an object contour tracking algorithm using snakes in stereo image sequences. The proposed technique is composed of two steps. In the first step, the candidate Snake points are determined from the motion information in 3-D disparity space. In the second step, the energy of Snake function is calculated to check whether the candidate Snake points converge to the edges of the interested objects. The energy of Snake function is calculated from the candidate Snake points using the disparity information obtained by patch matching. The performance of the proposed technique is evaluated by applying it to various sample images. Results prove that the proposed technique can track the edges of objects of interest in the stereo image sequences even in the cases of complicated background images or additive components.