• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1080-1088
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• 2004

In this paper, the interesting moving objects tracking algorithm using color information on Multi-Video camera against variance of intensity, shape and background is proposed. Moving objects are detected by using difference image method and integral projection method to background image and objects image only with hue area, after converting RGB color coordination of image which is input from multi-video camera into HSI color coordination. Hue information of the detected moving area are segmented to 24 levels from $0^{\circ}$ to $360^{\circ}$. It is used to the feature parameter of the moving objects that are three segmented hue levels with the highest distribution and difference among three segmented hue levels. To examine propriety of the proposed method, human images with variance of intensity and shape and human images with variance of intensity, shape and background are targeted for moving objects. As surveillance results of the interesting human, hue distribution level variation of the detected interesting human at each camera is under 2 level, and it is confirmed that the interesting human is tracked and surveilled by using feature parameters at cameras, automatically.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.181-191
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• 2002

Video based surveillance systems based on an active camera require a fast algorithm for real time detection and tracking of local motion in the presence of global motion. This paper presents a new fast and efficient motion detection and tracking algorithm using the displaced frame difference (DFD). In the Proposed algorithm, first, a Previous frame is adaptively selected according to the magnitude of object motion, and the global motion is estimated by using only a few confident matching blocks for a fast and accurate result. Then, a DFD is obtained between the current frame and the selected previous frame displaced by the global motion. Finally, a moving object is extracted from the noisy DFD by utilizing the correlation between the DFD and current frame. We implement this algorithm into an active camera system including a pan-tilt unit and a standard PC equipped with an AMD 800MHz processor. The system can perform the exhaustive search for a search range of 120, and achieve the processing speed of about 50 frames/sec for video sequences of 320$\times$240. Thereby, it provides satisfactory tracking results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.819-822
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• 2007

In this paper, we propose an object-tracking of mobile robots using CHT(Circular Hough transform) algorithm. The proposed method extracts the region of moving objects using 1-D projection algorithm, and detects circular objects using CHT. In order to verify the effectiveness of the proposed tracking method, we perform experiments of ball shape object-tracking using mobile robot based on ARM processor with CMOS camera.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.664-666
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• 1999

영상 추적(visual tracking)은 로봇의 시각기반제어, 교통정보시스템, 무인감시시스템 등 다양한 분야에 적용 가능하기 때문에 지정된 혹은 운동이 감지된 물체를 지속적이고 빠르게 추적하는 데 목적을 둔다. 이 때 어려운 문제 중 하나는 시간이 지나면서 위치이동은 물론 회전에 와해 물체의 모양이 변한다는 것이다. 이에 본 논문에서는 물체의 3차원 회전에 대응 가능한 실시간 영상추적 알고리듬을 제안한다. 이 알고리듬은 SSD(sum-of-squared differences)를 기반으로 하되, 물체의 배경이 바뀔 때나 물체가 영상추적 윈도우보다 작은 경우에도 추적이 가능하고 3차원 회전에 대응 가능하다. 이것은 3차원 회전으로 인하여 추적목표를 잃어버리는 것을 막기 위하여 기준 영역이 회전할 때 제안된 성능지수에 따라 영상추적 영역과 기준 영상을 새롭게 설정해줌으로써 구현된다. 제안된 알고리듬은 PC기반 실시간 시각시스템에서 성공적으로 실험되었다.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1999-2000
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• 2006

기존 2D 추적기들은 영상에서 특정 평면 영역을 원근 투영하에서 만족할 만한 추적결과를 보여주었다. 하지만 2D 추적기는 2D 영역들로 이루어진 3D물체를 영상에서 추적하는 경우, 물체자신의 회전에 의해 가려지거나 새로 나타나는 영역에 대해 대응하지 못하여 추적에 실패하게 되지만, 3D 정보를 이용한다면 이러한 사라짐과 나타나는 영역을 예측하고 완벽하게 추적할 수 있게 된다. 본 연구에서는 일련의 영상으로부터 3D 모델과 2D 텍스쳐맵을 추출하고, 이를 이용하여 3D 물체의 회전과 평행이동 움직임을 추적한다. 또한 카메라의 줌 파라미터를 모델링하고 추적기 알고리즘에 추가하여, 물체의 3차원 파라미터의 추적과 동시에 카메라 줌 파라미터를 추적하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.205-208
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• 2006

The position tracking of moving image for surveillance system is presented in this paper. The image of objects moving is detected with difference image between the background image not to be moved relatively and the forward moving image. The moving image is tracked with edge detection and moving vector to the object. The experiment result shows that the system enable to trail the position of moving objects obviously and is able to discriminate an infiltration.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.743-748
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• 2011

In this paper, we propose a collaborative tracking algorithm for intelligent video surveillance systems using the multiple network cameras. To do this, each camera detects a moving object and it's movement direction by motion templates. Once a moving object is detect, the Kalman filter is used to reduce noises, and a collaborative tracking camera is selected according to the movement direction and the camera state. In this procedure, Pan-Tilt-Zoom(PTZ) parameters are assigned to obtain clear images. Finally, some experiments show the validity of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.112-118
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• 2014

This paper deals with a color-based tracking of a moving object. Firstly, existing Camshift algorithm is complemented to improve the tracking weakness in the brightness change of an image which occurs in every frame. The complemented Camshift still shows unstable tracking when the objects with same color of the tracking object exist in background. In order to overcome the drawback this paper proposes the Camshift combined with KLT algorithm based on optical flow. The KLT algorithm performing the pixel-based feature tracking can complement the shortcoming of Camshift. Experimental results show that the merged tracking method makes up for the drawback of the Camshit algorithm and also improves tracking performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.318-322
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• 2006

본 연구에서는 한정된 전원으로 구동되는 센서 네트워크 환경 하에서 물체의 이동을 검출하고 예측을 통해 효과적인 추적을 가능케 함으로써 missing-rate를 최소로 하는 새로운 형태의 알고리즘을 제안하고 시뮬레이션을 통해 제안된 방법의 유용성을 입증하고자 한다. 제안된 기법에서는 물체의 이동과 관련된 센서 노드들로부터의 정보 및 이를 기반으로 센서 노드에 장착된 A/D변환기의 임계값을 적응적으로 변화시킴으로써 물체의 missing-rate를 최소화 시키고자 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.868-871
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• 2009

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.