• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• Journal of Korea Game Society
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• v.12 no.1
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• pp.57-65
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• 2012

Interactive games allow users to obtain embodied experience using the bodies as controllers. The same is true in interactive media arts where users engage in active participation. In contrast to video games, physical body feedback is desired and such practice can be found in robotic arts. I suggest that interactive media arts and interactive games should share common foundations. In this context, I introduce and explain an interactive robotic art work implemented. This work is a musical instrument that employs a robot which travels sitting on two strings in response to audience positions. In results, the robot modulates the vibrations of the strings by causing the effective lengths of the strings changed. The robot uses an economic multi-cell proximity sensor in order to track the audience. In the interaction, phenomenological tension could take place in the performative narrative space. In this paper, I discuss this interactive robotic work in the context of interactive games with a few examples.

• Journal of Chest Surgery
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• v.34 no.5
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• pp.393-398
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• 2001

배경: 일차성 자연기흉의 재발방지를 위해서 폐기포절부위에 흡수성 셀룰로스망사와 Fibrin gluefm 도포하여 수술후 재발율을 줄일 수 있는 지 알아보았다. 대상 및 방법: 1996.4우러부터 2000.6월까지 2명의 술자가 222례의 일차성 자연기흉을 수술하였으며, 수술시기와 치료방법에 따라 4군으로 나누어 비교하였다. 제1군은 1996년부터 1997년가지 비디오흉강경수술 및 기계적 늑막유착술로 시술받은 군(25례), 제 2군은 같은 기간동안 액와개흉술 및 늑막유착술로 시술받은 군(53례), 제 3군은 1998년부터 2000.4월까지 흉강경수술 및 늑만유착술로시술받은 군(110례), 제 4군은 1999.7월부터 2000.6월까지 흉강경수술 및 봉합부위를 셀룰로스망사와 Fibrin glue로 보강한 군(34례)이었다. 각 군간, 엑스선상 기흉의 크기 및 폐기포의 수나 크기에 따라 재발율, 공기누출시간 및 흉관지속지간등을 일반선형모델을 사용하여 비교 분석하였다. 결과: 대상환자는 남자 203례, 여자 19례 이었고, 나이는 14게에서 68세이었고, 평균연령은 23.2$\pm$9.6세였다. 재발한 경우는제 1군이 5례(25%), 제 2군이 2례(3.8%), 제 3군이 5례(4.5%)이었고, 제 4군은 재발례가 없었다. 재발례는 모두 수술자의 수술경험이 2년이내일 때 발생하였다. 흉관지속기간은 제 4군이 제 3군(p<0.0006) 및 제1, 제2군(p<0.0001)에 비해서 더 짧았고, 술후 공기누출이 제 4군에서는 없었다. 술전흉부엑스선상 기흉의 크기에 따른 수술후 기흉의 재발울은 경도의 기흉에서 14.3%(2/14)이었고, 중등도 기흉에서 7.4%(10/134)이었으며, 심한 기흉에서는 재발례가 없었다. 재수술한 12례중 봉합부위근처에서 기포가 발행된 경우가 9례(75%)로 많았다. 결론: 재발방지를 위한 시술로 늑막유착술을 시행하지 않고 폐기포절제부위를 흡수성 셀룰로스망사와 Fibrin glue로 덮어주는 시술은 비교적 용이하며, 수술 후 공기 누출이 없었고, 수술 후 흉관지속기간이 더 짧았고, 단기간 추적에서 재발이 없었다. 재발에 영향을 미치는 것으로 흉부엑스선상 기흉의 크기가 작은 경우에는 재발율이 더 높았고, 수술자의 경험이 중요하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.160-166
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• 2020

As mobile-based hardware technology develops, many kinds of applications are also being developed. In addition, there is an increasing demand to automatically check that the interface of these applications works correctly. In this paper, we describe a method for accurately detecting faulty images from applications by comparing major characteristics from input color images. For this purpose, our method first extracts major characteristics of the input image, then calculates the differences in the extracted major features, and decides if the test image is a normal image or a faulty image dissimilar to the reference image. Experiment results show that the suggested approach robustly determines similar and dissimilar images by comparing major characteristics from input color images. The suggested method is expected to be useful in many real application areas related to computer vision, like video indexing, object detection and tracking, image surveillance, and so on.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.145-153
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• 2009

Trajectory data are ubiquitous in the real world. Recent progress on satellite, sensor, RFID, video, and wireless technologies has made it possible to systematically track object movements and collect huge amounts of trajectory data. Accordingly, there is an ever-increasing interest in performing data analysis over trajectory data. In this paper, we develop a data mining tool for massive trajectory data. This mining tool supports three operations, clustering, classification, and outlier detection, which are the most widely used ones. Trajectory clustering discovers common movement patterns, trajectory classification predicts the class labels of moving objects based on their trajectories, and trajectory outlier detection finds trajectories that are grossly different from or inconsistent with the remaining set of trajectories. The primary advantage of the mining tool is to take advantage of the information of partial trajectories in the process of data mining. The effectiveness of the mining tool is shown using various real trajectory data sets. We believe that we have provided practical software for trajectory data mining which can be used in many real applications.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.135-139
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• 2012

The wide diffusion of internet and the overall increased reliance on technology for information communication, dissemination and gathering have created an unparalleled mass of data. Sifting through this data is defining and will define in the foreseeable future a big part of contemporary computer science. Within this data, a growing proportion is given by personal information, which represents a unique opportunity to study human activities extensively and live. One important recurring challenge in many disciplines is the problem of people re-identification. In its broadest definition, re-identification is the problem of newly recognizing previously identified people, such as following an unknown person while he walks through many different surveillance cameras in different locations. Our goals is to review how several diverse disciplines define and meet this challenge, from person re-identification in video-surveillance to authorship attribution in text samples to distinguishing users based on their preferences of pictures. We further envision a situation where multidisciplinary solutions might be beneficial.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.1
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• pp.22-29
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• 2010

A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1139-1149
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• 2006

This paper describes a novel and efficient algorithm, which extracts focused objects from still images with low depth-of-field (DOF). The algorithm unfolds into four modules. In the first module, a HOS map, in which the spatial distribution of the high-frequency components is represented, is obtained from an input low DOF image [1]. The second module finds OOI candidate by using characteristics of the HOS. Since it is possible to contain some holes in the region, the third module detects and fills them. In order to obtain an OOI, the last module gets rid of background pixels in the OOI candidate. The experimental results show that the proposed method is highly useful in various applications, such as image indexing for content-based retrieval from huge amounts of image database, image analysis for digital cameras, and video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing system.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.119-126
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• 2007

This paper presents a study investigating the effects of VR learning style on user attention and memory. The study involved users performed the guided or unguided style learning in the virtual environment while user attention was measured through physiological sensors (EEG, ECG, and GSR) and an eye tracking system. The users experienced the five specific events in a virtual environment associated with different stimuli, while they were given more specific goals during the guided task whereas they were given more goal asking them to actively search for the interesting items during the unguided task. The subject's attentions workload, feelings, memories about VR experience were measured by using a variety of physiological sensors during the task, video analysis, and post test survey. The results showed that the unguided task followed by the guided task made a considerable learning effect by giving a preview effect to the user. Moreover, the guided task drew more user attention and mental workload than the unguided task did.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.1-10
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• 2019

Object-based image matching algorithms have been widely used in the image processing and computer vision fields. A variety of applications based on image matching algorithms have been recently developed for object recognition, 3D modeling, video tracking, and biomedical informatics. One prominent example of image matching features is the Scale Invariant Feature Transform (SIFT) scheme. However many applications using the SIFT algorithm have implemented based on stand-alone basis, not client-server architecture. In this paper, We initially implemented based on client-server structure by using SIFT algorithms to identify and match objects in biomedical images to provide useful information to the user based on the recently released Mobile platform. The major methodological contribution of this work is leveraging the convenient user interface and ubiquitous Internet connection on Mobile device for interactive delineation, segmentation, representation, matching and retrieval of biomedical images. With these technologies, our paper showcased examples of performing reliable image matching from different views of an object in the applications of semantic image search for biomedical informatics.