• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1171-1177
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• 2021

Measuring and evaluation of audience's visual message perception are crucial process for scientific production of visual content. This study tried to evaluate the difference of viewer's awareness of visual object depends on his or her inherent characteristics like conservatism using an eye tracker system. Especially, this experiment tested research questions about positive correlation between conservatism and peoples' eye movements following the sound visual messages. 57 subjects participated in the test. Two different groups were exposed to two visual elements representing 'the conservative' and 'the liberal'. The results showed that people tended to have different way of seeing visual objects according to their inherent characteristics. Also by comparing the gaze time at the object and area of interest(AOI) in visual, this study is able to verify the existence of 'positive way of seeing' and 'negative way of seeing'. The two different ways of seeing have their own trail of eye movement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• 한국자동차공학회논문집
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• 제24권2호
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.113-118
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• 1997

This paper proposes a object tracking method based on the local moments, or moment based on the local moments, or moment of some restricted area, in which the idea of the viewpoint and the visual filed corresponding to the local area of an image is introduced. Using local moment with the optimally controlled viewpoint and visual field, the target position and its breadth are estimated robustly. By two experiments, the validity of the proposed method is shown.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1917-1920
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• 2003

Automatic tracking of a moving object such as a person is a demanding technique especially in surveillance. This paper describes an experimental system for tracking a moving object on the ground by using a visually controlled aerial robot. A blimp is used as the aerial robot in the proposed system because of its locality in motion and its silent nature. The developed blimp is equipped with a camera for taking downward images and four rotors for controlling the progression. Once a camera takes an image of a specified moving object on the ground, the blimp is controlled so that it follows the object by the employment of the visual information. Experimental results show satisfactory performance of the system. Advantages of the present system include that images from the air often enable us to avoid occlusion among objects on the ground and that blimp’s progression is much less restricted in the air than, e.g., a mobile robot running on the ground.

• 반도체디스플레이기술학회지
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• 제10권1호
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• pp.83-89
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• 2011

In the case of the tracking system with an active camera, it is very difficult to guarantee real-time processing due to the attribute of vision system which handles large amounts of data at once and has time delay to process. The reliability of the processed result is also badly influenced by the slow sampling time and uncertainty caused by the image processing. In this paper, we figure out dynamic characteristics of pixels reflected on the image plane and derive the mathematical model of the vision tracking system which includes the actuating part and the image processing part. Based on this model, we find a controller that stabilizes the system and enhances the tracking performance to track a target rapidly. The centroid is used as the position index of moving object and the DC motor in the actuating part is controlled to keep the identified centroid at the center point of the image plane.

• 한국산학기술학회논문지
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• 제6권4호
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• pp.349-354
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• 2005

컴퓨터 비전에 관한 연구는 인간의 시각 능력을 대신할 시스템을 구축하고자 하는 것으로 특히 이동 객체추적 시스템은 최근 중요한 연구 분야로 대두되고 있다. 본 연구에서는 움직임 추정에 기반 한 단일 이동객체를 추적할 수 있는 시스템을 제안하였다. 추적 시스템은 차영상 기법을 이용하여 객체의 움직임을 추정하곤 카메라의 Pan/Tilt를 제어함으로서 이동 객체를 추적할 수 있도록 하였다. 구현된 시스템은 영상획득 및 전처리 단계, 움직임 추정 단계, 객체 추적 단계로 구성하였다. 실시간 추적 실험을 실시한 결과 이동 객체의 움직임을 추정할 수 있었고, 추적 과정에서도 객체를 일어버리지 앉고 정상적으로 추적할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2995-2997
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• 1999

Recently, real-time visual tracking control for a robot manipulator is performed by using a vision feedback sensor information. In this paper, the optical flow is computed based on the eye-in-hand robot configuration. The image jacobian is employed to calculate the rotation and translation velocity of a 3D moving object. LQG visual controller generates the real-time visual trajectory. In order to improving the visual tracking performance. VSC controller is employed to control the robot manipulator. Simulation results show a better visual tracking performance than other method.

• 한국멀티미디어학회논문지
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• 제24권6호
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• pp.796-804
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• 2021

In computer vision, visual tracking method addresses the problem of localizing an specific object in video sequence according to the bounding box. In this paper, we propose a tracking method by introducing the feature correlation comparison into the siamese network to increase its matching identification. We propose a way to compute location of object to improve matching performance by a correlation operation, which locates parts for solving the searching problem. The higher layer in the network can extract a lot of object information. The lower layer has many location information. To reduce error rate of the object center point, we built a siamese network that extracts the distribution and location information of target objects. As a result of the experiment, the average center error rate was less than 25%.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2120-2123
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• 2003

This paper presents the moving object detection and tracking algorithm using edge information base on human perceptual system The human visual system recognizes shapes and objects easily and rapidly. It's believed that perceptual organization plays on important role in human perception. It presents edge model(GCS) base on extracted feature by perceptual organization principal and extract edge information by definition of the edge model. Through such human perception system I have introduced the technique in which the computers would recognize the moving object from the edge information just like humans would recognize the moving object precisely.