• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.146-153
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• 2009

Thanks to computer graphic technology development, graphic design programming is easily accessible by any home computer user today since it is free from the burdens of complicated 알고리듬 or the expensive graphic tools that were required in the past. The term 알고리듬 2.5 is commonly used by computer graphic designers to refer to 2D, a form of pseudo-3D. In this study, by using 2.5D, which was previously utilized for strengthening visual effects and engine efficiency, together with Adobe Photoshop along with After Effects, I will incorporate these into motion graphics. Today, motion graphics dominate the advertisement and image markets. Since viewers have developed higher expectations, a more dynamic 3D space graphic technology is preferred over the outdated 2D basis. In this study, I will produce a 2.5D image which is generated through a vanishing point filter of Adobe Photoshop and After Effects based on still image information and captured at an angle of Axonometric Projection. Also, I will compare the effectiveness of the production process and camera angle flexibility between the previous 3D process and new 2.5 D process.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1828-1836
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• 2015

Object tracking algorithms can reduce computational cost by avoiding computation over the whole image through the selection of region of interests based on object detection. So, accurate object detection is an important task for object tracking. The background subtraction algorithm has been widely used in moving object detection using a stationary camera. However, it has the problem of object detection error due to incorrect background modeling, whereas the method of background modeling has been improved by many researches. This paper proposes a new moving object detection algorithm to overcome the drawback of the conventional background subtraction algorithm by combining the background subtraction algorithm with the motion history image algorithm that is usually used in gesture detection. Although the proposed algorithm demands more processing time because of time taken for combining two algorithms, it meet the real-time processing requirement. Moreover, experimental results show that it has higher accuracy compared with the previous two algorithms.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.2
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• pp.128-133
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• 2015

This paper describes the construction of a static 3D ultrasonography image by tracking the radiation beam position during the handy operation of a 1D array probe to enable point-of-care use. The theoretical model of the transformation from the translational and rotational information of the sensor mounted on the probe to the reference Cartesian coordinate system was given. The signal amplification and serial communication interface module was made using a commercially available sensor. A test phantom was also made using silicone putty in a donut shape. During the movement of the hand-held probe, B-mode movie and sensor signals were recorded. B-mode images were periodically selected from the movie, and the gray levels of the pixels for each image were converted to the gray levels of 3D voxels. 3D and 2D images of arbitrary cross-section of the B-mode type were also constructed from the voxel data, and agreed well with the shape of the test phantom.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.69-76
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• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.45-52
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• 2022

A tangible sports game is an exercise game that uses sensors or cameras to track the user's body movements and to feel a sense of reality. Recently, VR indoor sports room systems installed to utilize tangible sports game for physical activity in schools. However, these systems primarily use screen-touch user interaction. In this research, we developed a V-Catch Vision system that uses AI image recognition technology to enable tracking of user movements in three-dimensional space rather than two-dimensional wall touch interaction. We also conducted a usability evaluation experiment to investigate the exercise effects of this system. We tried to evaluate quantitative exercise effects by measuring blood oxygen saturation level, the real-time ECG heart rate variability, and user body movement and angle change of Kinect skeleton. The experiment result showed that there was a statistically significant increase in heart rate and an increase in the amount of body movement when using the V-Catch Vision system. In the subjective evaluation, most subjects found the exercise using this system fun and satisfactory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.587-588
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• 2022

In this paper, we propose a rigid body tracking method in 3D space using 2D passive marker images from multiple motion capture cameras. First, a calibration process using a chess board is performed to obtain the internal variables of individual cameras, and in the second calibration process, the triangular structure with three markers is moved so that all cameras can observe it, and then the accumulated data for each frame is calculated. Correction and update of relative position information between cameras. After that, the three-dimensional coordinates of the three markers were restored through the process of converting the coordinate system of each camera into the 3D world coordinate system, the distance between each marker was calculated, and the difference with the actual distance was compared. As a result, an error within an average of 2mm was measured.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.930-939
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• 2010

Recently, many researches for making more comfortable input device based on gaze detection have been vigorously performed in human computer interaction. However, these previous researches are difficult to be used in IPTV environment because these methods need additional wearing devices or do not work at a distance. To overcome these problems, we propose a new way of controlling IPTV interface by using a detected face and eye positions in single static camera. And although face or eyes are not detected successfully by using Adaboost algorithm, we can control IPTV interface by using motion vectors calculated by pyramidal KLT (Kanade-Lucas-Tomasi) feature tracker. These are two novelties of our research compared to previous works. This research has following advantages. Different from previous research, the proposed method can be used at a distance about 2m. Since the proposed method does not require a user to wear additional equipments, there is no limitation of face movement and it has high convenience. Experimental results showed that the proposed method could be operated at real-time speed of 15 frames per second. Wd confirmed that the previous input device could be sufficiently replaced by the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.110-116
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• 2016

Autonomous vehicles must obey the traffic laws in order to drive actual roads. Traffic signs erected at the side of roads explain the road traffic information or regulations. Therefore, traffic sign recognition is necessary for the autonomous vehicles. In this paper, color characteristics are first considered to detect traffic sign candidates. Subsequently, we establish HOG (Histogram of Oriented Gradients) features from the detected candidate and recognize the traffic sign through a SVM (Support Vector Machine). However, owing to various circumstances, such as changes in weather and lighting, it is difficult to recognize the traffic signs robustly using only SVM. In order to solve this problem, we propose a tracking algorithm with RANSAC-based motion estimation. Using two-point motion estimation, inlier feature points within the traffic sign are selected and then the optimal motion is calculated with the inliers through a bundle adjustment. This approach greatly enhances the traffic sign recognition performance.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.430-443
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• 2003

The objective of this paper is to evaluate most useful feature vector space using the angle, velocity and location features from gesture trajectory which extracted hand regions from consecutive input images and track them by connecting their positions. For this purpose, the gesture tracking algorithm using color and motion information is developed. The recognition module is a HMM model to adaptive time various data. The proposed algorithm was applied to a database containing 4,800 alphabetical handwriting gestures of 20 persons who was asked to draw his/her handwriting gestures five times for each of the 48 characters.