• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.633-637
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• 2001

In this paper, we proposed model creation algorithm for multiple moving objects tracking. The proposed algorithm is divided that the initial model creation step as moving objects are entered into background image and the model reformation step in the moving objects tracking step. In the initial model creation step, the initial model is created by AND operating division image, divided using difference image and clustering method, and edge image of the current image. In the model reformation step, a new model was reformed in the every frame to adapt appearance change of moving objects using Hausdorff Distance and 2D-Logarithmic searching algorithm. We simulated for driving cart in the road. In the result, model was created over 98% in case of irregular approach direction of cars and tracking objects number.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.834-848
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• 2013

To effectively use these functions many kinds of human-phone interface are used such as touch, voice, and gesture. However, the most important touch interface cannot be used in case of hand disabled person or busy both hands. Although eye tracking is a superb human-computer interface method, it has not been applied to smartphones because of the small screen size, the frequently changing geometric position between the user's face and phone screen, and the low resolution of the frontal cameras. In this paper, a new eye tracking method is proposed to act as a smartphone user interface. To maximize eye image resolution, a zoom lens and three infrared LEDs are adopted. Our proposed method has following novelties. Firstly, appropriate camera specification and image resolution are analyzed in order to smartphone based gaze tracking method. Secondly, facial movement is allowable in case of one eye region is included in image. Thirdly, the proposed method can be operated in case of both landscape and portrait screen modes. Fourthly, only two LED reflective positions are used in order to calculate gaze position on the basis of 2D geometric relation between reflective rectangle and screen. Fifthly, a prototype mock-up design module is made in order to confirm feasibility for applying to actual smart-phone. Experimental results showed that the gaze estimation error was about 31 pixels at a screen resolution of $480{\times}800$ and the average hit ratio of a $5{\times}4$ icon grid was 94.6%.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.362-371
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• 2013

This paper presents a framework of real-time augmented reality on 3-D mobile display with stereo camera tracking. In the framework, camera poses are jointly estimated with the geometric relationship between stereoscopic images, which is based on model-based tracking. With the estimated camera poses, the virtual contents are correctly augmented on stereoscopic images through image rectification. For real-time performance, stereo camera tracking and image rectification are efficiently performed using multiple threads. Image rectification and color conversion are accelerated with a GPU processing. The proposed framework is tested and demonstrated on a commercial smartphone, which is equipped with a stereoscopic camera and a parallax barrier 3-D display.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.86-92
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• 2007

A discrete dynamic model for tracking feature points in 2D images is developed. Conventional snake approaches deform a contour to lock onto features of interest within an image by finding a minimum of its energy functional, composed of internal and external forces. The neighborhood around center snaxel is a space matrix, typically rectangular. The structure of the model proposed in this paper is a set of connected vertices. Energy model is designed for its local minima to comprise the set of alternative solutions available to active process. Block on tracking is one dimension, line type. Initial starting points are defined to the satisfaction of indent states, which is then automatically modified by an energy minimizing process. The track is influenced by curvature constraints, ascent/descent or upper/lower points. The advantages and effectiveness of this layer approach may also be applied to feature points tracking of digital image whose pixels have one directional properties with high autocorrelation between adjacent data lines, vertically or horizontally. The test image is the ultrasonic carotid artery image of human body, and we have verified its effect on intima/adventitia starting points tracking.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1211-1212
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• 2008

In this paper, we propose image process modeling as a part of location based surveillance system for unauthorized target recognition and tracking in harbor, airport, military zone. For this, we compress and store background image in lower resolution and perform object extraction and motion tracking by using sobel edge detection and difference picture method between real images and a background image. In addition to, we use Independent Component Analysis Neural Network for moving target recognition. Experiments are performed for object extraction and tracking of moving targets on road by using static camera in 20m height building and it shows the robust results.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.615-618
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• 1999

In this paper, a object detection and tracking algorithm is presented which exhibits robust properties for image sequences with complex background. The proposed algorithm is composed of three parts: moving object detection, object tracking, and motion analysis. The moving object detection algorithm is implemented using a temporal median background method which is suitable for real-time applications. In the motion analysis, we propose a new technique for removing a temporal clutter, such as a swaying plant or a light reflection of a background object. In addition, we design a multiple vehicle tracking system based on Kalman filtering. Computer simulation of the proposed scheme shows its robustness for MPEG-7 test image sequences.

• Journal of Sensor Science and Technology
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• v.18 no.3
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• pp.190-196
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• 2009

In a conventional camera system, a target tracking system consists of a camera part and a image processing part. However, in the field of the real time image processing, the vision chip for edge detection which was made by imitating the algorithm of humanis retina is superior to the conventional digital image processing systems because the human retina uses the parallel information processing method. In this paper, we present a high speed target tracking system using the function of the CMOS vision chip for edge detection.

• The Journal of Korea Robotics Society
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• v.2 no.1
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• pp.21-28
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• 2007

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.129-136
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• 2007

This paper introduces a position-based robust visual servoing method which is developed for operation of a human-like robot with two arms. The proposed visual servoing method utilizes SIFT algorithm for object detection and CAMSHIFT algorithm for object tracking. While the conventional CAMSHIFT has been used mainly for object tracking in a 2D image plane, we extend its usage for object tracking in 3D space, by combining the results of CAMSHIFT for two image plane of a stereo camera. This approach shows a robust and dependable result. Once the robot's task is defined based on the extracted 3D information, the robot is commanded to carry out the task. We conduct several position-based visual servoing tasks and compare performances under different conditions. The results show that the proposed visual tracking algorithm is simple but very effective for position-based visual servoing.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.49-57
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• 2016

In this paper, we propose the novel tracking method which uses the weighted discriminative correlation filter (DCF). We also propose the PSPR instead of conventional PSR as tracker performance evaluation method. The proposed tracking method uses multiple DCF to estimates the target position. In addition, our proposed method reflects more weights on the correlation response of the tracker which is expected to have more performance using PSPR. While existing multi-DCF-based tracker calculates the final correlation response by directly summing correlation responses from each tracker, the proposed method acquires the final correlation response by weighted combining of correlation responses from the selected trackers robust to given environment. Accordingly, the proposed method can provide high performance tracking in various and complex background compared to multi-DCF based tracker. Through a series of tracking experiments for various video data, the presented method showed better performance than a single feature-based tracker and also than a multi-DCF based tracker.