• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• Information and Communications Magazine
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• v.28 no.4
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• pp.35-40
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• 2011

본고에서는 지능형 국방 감시시스템에 적용할 수 있는 핵심 기술인 PTZ(Pan-Tilt-Zoom) 네트워크 카메라를 이용한 액티브 객체 추적 및 객체 특성 분석 기법을 소개한다. 본고에서 소개하는 기법은 기존의 적응적 배경 모델링 기반의 객체 검출에서 발생하는 고스트 현상을 제거하고 정지객체를 안정적으로 추적할 수 있는 방법과 PTZ 카메라의 Panning, Tilting, Zooming을 통하여 카메라의 FOV를 지속적으로 추적하기 위한 카메라 이동 위치 예측 알고리즘을 포함하고 있다. 본고에서는 또한, 지능형 감시시스템의 한 종류로서 일반인이 통행할 수 있는 구역에서 출입자의 의상 특성을 분석하여 비인증 출입자를 검출하는 방법과 추적하는 객체가 차량일 경우, 차량의 종류를 자동 분류하는 기법을 소개한다.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.802-812
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• 2019

With the rapid development in the field of unmanned aerial vehicles(UAVs) and drones, higher request to development of a surveillance system for a drone is putting forward. Since surveillance systems with fixed cameras have a limited range, a development of surveillance systems with a moving camera applicable to PTZ(Pan-Tilt-Zoom) cameras is required. Selecting the features for object plays a critical role in tracking, and the object has to be represented by their shapes or appearances. Considering these conditions, in this paper, an object tracking method with optical flow is introduced to track a tiny drone with a moving camera. In addition, a tracking method combined with kalman filter is proposed to track continuously even when tracking is failed. Experiments are tested on sequences which have a target from the minimal 12 pixels to the maximal 56337 pixels, the proposed method achieves average precision of 175% improvement. Also, experimental results show the proposed method tracks a target which has a size of 12pixels.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.245-248
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• 2001

본 논문은 히스토그램 백 프로젝션, 히스토그램 인터 섹션 그리고 XY-프로젝션을 이용하여 물체를 분할하고 정합하여 물체 추적 시스템에 적용하고자 한다. 물체 추적 시스템에서 실시간 처리를 위하여 물체정합 모델은 계산량이 적고, 물체의 변화에도 일관성이 있어야 한다. 본 논문에서 제안한 물체정합 모델은 이러한 물체 추적 시스템에 적합하다. 본 논문에서는 움직이는 카메라로부터 획득된 영상에서 물체를 정합하는 것을 보였으며, 물체를 큰 오차 없이 추적함을 보였다.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1228-1238
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• 2003

This paper presents a new and practical method based on computer vision for detecting the monitor position where the user is looking. In general, the user tends to move both his face and eyes in order to gaze at certain monitor position. Previous researches use only one wide view camera, which can capture a whole user's face. In such a case, the image resolution is too low and the fine movements of user's eye cannot be exactly detected. So, we implement the gaze detection system with dual camera systems(a wide and a narrow view camera). In order to locate the user's eye position accurately, the narrow view camera has the functionalities of auto focusing and auto panning/tilting based on the detected 3D facial feature positions from the wide view camera. In addition, we use dual R-LED illuminators in order to detect facial features and especially eye features. As experimental results, we can implement the real-time gaze detection system and the gaze position accuracy between the computed positions and the real ones is about 3.44 cm of RMS error.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.611-613
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• 2015

Multimedia classroom teaching as well as the automatic tracking of the camera are automatically saved track to be saved. The existing tracking system is attached to the body by a separate sensor to track or on the front of the sensor to the construction of the track was a hit at the same time in front of the discomfort caused by tracking errors when I had an issue that shouldn't be. In this paper, Microsoft-Kinect sensor, using the speaker's position and behavior analysis (instructor), and PTZ cameras, recording systems, storage classes and lectures with classroom lessons can be effective at the time of recording to the content production about the technology of unmanned speaker tracking solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3C
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• pp.271-277
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• 2010

In this paper we proposed an object tracking system using PTZ camera. Once the target object is detected, the CAMshift tracking algorithm focuses it in realtime mode as the camera is moving accordingly. Since the CAMShift algorithm takes into account the object size, zoom related tracking is possible. We used the spherical coordinate to gain pan and tilt position. The position information is used to set the center of target object in the middle of the image by using the PTZ protocol and RS-485 interface. Our system showed excellent experimental results in various environments.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.937-944
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• 2007

In this paper, we propose multiple human tracking with an moving stereo camera. The tracking process is based on mean shift algorithm which is using color information of the target. Color based tracking approach is invariant to translation and rotation of the target but, it has several problems. Because of mean shift uses color distribution, it is sensitive to color distribution of background and targets. In order to solve this problem, we combine color and depth information of target. Also, we build human body part model to handle occlusions and we have created adaptive box scale. As a result, the proposed method is simple and efficient to track multiple humans in real time.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.173-181
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• 2004

In this paper, we propose a system for automatic moving object detection and tracking in sequence images acquired from a moving camera. The proposed algorithm consists of moving object detection and its tracking. Moving object can be detected by integration of BBME and DD method We segment the detected object using histogram back projection, match it using histogram intersection, extract and track it using XY-projection. Computer simulation results have shown that the proposed algorithm is reliable and can successfully detect and track a moving object on image sequences obtained by a moving camera.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.291-297
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• 2018

In this paper, we present an automatic image object tracking system for Studio cameras on the stage. For object tracking, we use the OpenCV-based Python program using PC, Raspberry Pi 3 and mobile devices. There are many methods of image object tracking such as mean-shift, CAMshift (Continuously Adaptive Mean shift), background modelling using GMM(Gaussian mixture model), template based detection using SURF(Speeded up robust features), CMT(Consensus-based Matching and Tracking) and TLD methods. CAMshift algorithm is very efficient for real-time tracking because of its fast and robust performance. However, in this paper, we implement an image object tracking system for studio cameras based CMT algorithm. This is an optimal image tracking method because of combination of static and adaptive correspondences. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the stage in real time.