• Archives of design research
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• v.19 no.2 s.64
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• pp.313-322
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• 2006

In this paper, we introduce 'Contents Based Image Retrieval' which helps a user find the images he or she needs more easily and reconfigures the images automatically. With this system, we try to realize the language of (motion) picture, that is, the Montage from the viewpoint of the user. The Real-time Montage System introduced in this paper uses 'Discrete Fourier Transform'. Through this, the user can find the feature of the image selected and compare the analogousness with the image in the database. This kind of system leads to the user's speedy and effective retrieving, Also, we can acquire the movement image of the user by Camera Tracking in Real-time. The movement image acquired is to be reconfigured automatically with the image of the user. In this way, we can get an easy and speedy image reconfiguration which sets to the user's intention. This system is a New Media Design tool(entertainment) which induces a user enjoy participating in it. In this system, Thus, the user is not just a passive consumer of one-way image channels but an active subject of image reproduction in this system. It is expected to be a foundation for a new style of user-centered movie (media based entertainment).

• Journal of the Semiconductor & Display Technology
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• v.15 no.2
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• pp.66-69
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• 2016

Recently, augmented reality and virtual reality in the ICT sector have been highlighted. So also interested in related HMD areas to facilitate contact with the VR content is being attend. This paper proposes a method for implementing to the virtual reality through the mobile HMD device with the real time 360 image. This system is required the real time 360 image streaming server configuration and image processing for augmented reality and virtual reality. The configuration of the streaming server is configured the DB server to store images and the relay server that can relay images to other devices. Augmented image processing module is composed based on markerless tracking, and there are four modules that are recognition, tracking, detecting and learning module. Also, the purpose of this paper is shown the augmented 360 image processing through the Mobile HMD.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.19-31
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• 2008

Video image processing systems(VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera such as flow and velocity, as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.537-542
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• 2011

A mirror neuron is a neuron fires both when an animal acts and when the animal observes the same action performed by another. We propose a method of 3D reconstruction for occluded object motion tracking like Mirror Neuron System to fire in hidden condition. For modeling system that intention recognition through fire effect like Mirror Neuron System, we calculate depth information using stereo image from a stereo camera and reconstruct three dimension data. Movement direction of object is estimated by optical flow with three-dimensional image data created by three dimension reconstruction. For three dimension reconstruction that enables tracing occluded part, first, picture data was get by stereo camera. Result of optical flow is made be robust to noise by the kalman filter estimation algorithm. Image data is saved as history from reconstructed three dimension image through motion tracking of object. When whole or some part of object is disappeared form stereo camera by other objects, it is restored to bring image date form history of saved past image and track motion of object.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.365-368
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• 2001

This work describes a real-time method, based on motion energy detection, for detecting and tracking moving object in the consecutive image sequences. The motion of moving objects is detected by taking the difference of the two consecutive image frames. In addition an edge information of the current image is utilized in order to further increase the accuracy of detection. We can track the moving objects continuously by detecting the motion of objects from the sequence of image frames. A prototype system has been implemented using a TI TMS320C6201 EVM fixed-point DSP board, which can successfully track a moving human in real-time.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.910-919
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• 2012

In this paper, we described development of on-board image processing system and its process and verified its performance through flight experiment. The image processing board has single ARM(Advanced Risk Machine) processor. We performed Embedded Linux Porting. Algorithm to be applied for object tracking is color-based image processing algorithm, it can be designed to track the object that has specific color on ground in real-time. To verify performance of the on-board image processing system, we performed flight test using the PNUAV, UAV developed by LAB. Also, we performed optimization of the image processing algorithm and kernel to improve real-time performance. Finally we confirmed that proposed system can track the blue-color object within four pixels error range consistently in the experiment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.2
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• pp.129-136
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• 2014

Target-tracking systems are important for carrying out effective surveillance missions using mobile surveillance robots. In this paper, we propose a target-tracking algorithm using camera image data for a three-axis mobile surveillance robot and carry out an actual hardware test for verifying the proposed algorithm. The heading direction vector of a camera system is deduced from the position error between the viewfinder center and the object center in a camera image. The position error is obtained using the CAMShift(Continuously Adaptive Mean Shift) algorithm, an image processing technique. The performance test of an actual three-axis mobile surveillance robot was carried out for verifying the proposed target-tracking algorithm in a real environment.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.167-174
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• 2013

TIn this paper, we find the face in color images and the ability to track the face was implemented. Face tracking is the work to find face regions in the image using the functions of the computer system and this function is a necessary for the robot. But such as extracting skin color in the image face tracking can not be performed. Because face in image varies according to the condition such as light conditions, facial expressions condition. In this paper, we use the skin color pixel extraction function added lighting compensation function and the entire processing system was implemented, include performing finding the features of eyes, nose, mouth are confirmed as face. Lighting compensation function is a adjusted sine function and although the result is not suitable for human vision, the function showed about 4% improvement. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, lips are detected. Face tracking efficiency was good.

• Journal of Advanced Navigation Technology
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• v.5 no.1
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• pp.26-36
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• 2001

One of the most important problems in time-varying image sequences is the automatic target tracking. This paper proposes a position prediction and tracking technique of moving object using fuzzy prediction. First, the object is segmented from background of the image using accumulative difference image technique. Then centroid of the segmented object is extracted by using the centroid method, and we propose to apply variable size searching window to the object in order to increase the tracking performance. Also, non-linear prediction is required for efficient object tracking. Therefore, in this paper, fuzzy prediction method is proposed for predicting the location of the moving object at next frame. An experimental result shows that the proposed fuzzy prediction system tracks the moving object in stable under various conditions.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.145-156
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• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.