• 한국항공운항학회지
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• 제18권2호
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• pp.16-22
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• 2010

This paper proposes the real-time moving object tracking system UAV using color information. Case of object tracking, it have studied to recognizing the moving object or moving multiple objects on the fixed camera. And it has recognized the object in the complex background environment. But, this paper implements the moving object tracking system using the pan/tilt function of the camera after the object's region extraction. To do this tracking system, firstly, it detects the moving object of RGB/HSI color model and obtains the object coordination in acquired image using the compact boundary box. Secondly, the camera origin coordination aligns to object's top&left coordination in compact boundary box. And it tracks the moving object using the pan/tilt function of camera. It is implemented by the Labview 8.6 and NI Vision Builder AI of National Instrument co. It shows the good performance of camera trace in laboratory environment.

• 대한인간공학회지
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• 제19권1호
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• pp.77-90
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• 2000

The aim of this study is to develop and evaluate an efficient camera calibration method for vision-based head tracking. Tracking head movements is important in the design of an eye-controlled human/computer interface. A vision-based head tracking system was proposed to allow the user's head movements in the design of the eye-controlled human/computer interface. We proposed an efficient camera calibration method to track the 3D position and orientation of the user's head accurately. We also evaluated the performance of the proposed method. The experimental error analysis results showed that the proposed method can provide more accurate and stable pose (i.e. position and orientation) of the camera than the conventional direct linear transformation method which has been used in camera calibration. The results of this study can be applied to the tracking head movements related to the eye-controlled human/computer interface and the virtual reality technology.

• International Journal of Internet, Broadcasting and Communication
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• 제10권1호
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• pp.16-22
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• 2018

This paper presents a solution for personal profiling system based on user-oriented tracking. Here, we introduce a new way to identify and track humans by using two types of cameras: dome and face camera. Dome camera has a wide view angle so that it is suitable for tracking human movement in large area. However, it is difficult to identify a person only by using dome camera because it only sees the target from above. Thus, face camera is employed to obtain facial information for identifying a person. In addition, we also propose a new mechanism to locate human on targeted location by using grid-cell system. These result in a system which has the capability of maintaining human identity and tracking human activity (movement) effectively.

• 대한임베디드공학회논문지
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• 제9권1호
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• pp.43-52
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• 2014

This paper presents a tracking system using images captured from a camera on a moving platform. A camera on an unmanned flying vehicle generally moves and shakes due to external factors such as wind and the ego-motion of the machine itself. This makes it difficult to track a target properly, and sometimes the target cannot be kept in view of the camera. To deal with this problem, we propose a new system for stable tracking of a target under such conditions. The tracking system includes target tracking and 3-axis camera motion compensation. At the same time, we consider the simulation of the motion of flying vehicles for efficient and safe testing. With 3-axis motion compensation, our experimental results show that robustness and stability are improved.

• Journal of Advanced Marine Engineering and Technology
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• 제29권5호
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• pp.560-570
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• 2005

In this paper, we discuss the tracking system for a wheelchair which can follow the path of a human target such as a nurse in hospital. The problem of human tracking is that it requires recognition of feature as well as the tracking of human positions. For this purpose the use of a high cost visual sensor such as laser finder or streo camera makes the tracking a high cost additional expense. This paper proposes the tracking system uses a low cost infrared range-finder and CCD camera, The Infrared range-finder and CCD camera can create a target candidate through each target recognition algorithm. and this information is fused in order to reduce the uncertainties of a target decision and correct the positional error of the human. The effectiveness of the proposed system is verified through experiments.

• 대한인간공학회지
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• 제16권3호
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• pp.1-10
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• 1997

This paper is concerned with the development and evaluation of the camera calibration method for a real-time head tracking system. Tracking of head movements is important in the design of an eye-controlled human/computer interface and the area of virtual environment. We proposed a video-based head tracking system. A camera was mounted on the subject's head and it took the front view containing eight 3-dimensional reference points(passive retr0-reflecting markers) fixed at the known position(computer monitor). The reference points were captured by image processing board. These points were used to calculate the position (3-dimensional) and orientation of the camera. A suitable camera calibration method for providing accurate extrinsic camera parameters was proposed. The method has three steps. In the first step, the image center was calibrated using the method of varying focal length. In the second step, the focal length and the scale factor were calibrated from the Direct Linear Transformation (DLT) matrix obtained from the known position and orientation of the camera. In the third step, the position and orientation of the camera was calculated from the DLT matrix, using the calibrated intrinsic camera parameters. Experimental results showed that the average error of camera positions (3- dimensional) is about $0.53^{\circ}C$, the angular errors of camera orientations are less than $0.55^{\circ}C$and the data aquisition rate is about 10Hz. The results of this study can be applied to the tracking of head movements related to the eye-controlled human/computer interface and the virtual environment.

• 방송공학회논문지
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• 제18권3호
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• pp.362-371
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• 2013

본 논문에서는 스테레오 카메라 추적을 이용한 모바일 3차원 디스플레이 상의 실시간 증강현실 프레임웍에 대하여 기술한다. 모델 기반 추적 방법에 기초하여 카메라 포즈는 스테레오 카메라 간의 기하 관계를 만족하도록 동시 추정된다. 동시 추정된 카메라 포즈를 통해 가상 콘텐츠는 교정된 스테레오 영상에 올바르게 증강된다. 스테레오 카메라 추적과 스테레오 영상 교정은 서로 다른 쓰레드에서 수행하고, 영상 형식 변환 및 스테레오 영상 교정은 GPU로 고속으로 처리함으로써 실시간으로 수행된다. 제안된 프레임웍은 스테레오 카메라와 3차원 디스플레이가 장착된 스마트폰에서 구현되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1287-1300
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• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1458-1463
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• 2004

Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

• IEIE Transactions on Smart Processing and Computing
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• 제1권2호
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• pp.78-87
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• 2012

In this paper, we address the tracking problem caused by camera motion and rolling shutter effects associated with CMOS sensors in consumer handheld cameras, such as mobile cameras, digital cameras, and digital camcorders. A modified particle filtering method is proposed for simultaneously tracking objects and compensating for the effects of camera motion. The proposed method uses an elastic registration algorithm (ER) that considers the global affine motion as well as the brightness and contrast between images, assuming that camera motion results in an affine transform of the image between two successive frames. By assuming that the camera motion is modeled globally by an affine transform, only the global affine model instead of the local model was considered. Only the brightness parameter was used in intensity variation. The contrast parameters used in the original ER algorithm were ignored because the change in illumination is small enough between temporally adjacent frames. The proposed particle filtering consists of the following four steps: (i) prediction step, (ii) compensating prediction state error based on camera motion estimation, (iii) update step and (iv) re-sampling step. A larger number of particles are needed when camera motion generates a prediction state error of an object at the prediction step. The proposed method robustly tracks the object of interest by compensating for the prediction state error using the affine motion model estimated from ER. Experimental results show that the proposed method outperforms the conventional particle filter, and can track moving objects robustly in consumer handheld imaging devices.