• Title/Summary/Keyword: 시각객체

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An Optimal Adaptation Framework for Transmission of Multiple Visual Objects (다중 시각 객체 전송을 위한 최적화 적응 프래임워크)

  • Lim, Jeong-Yeon;Kim, Mun-Churl
    • Journal of KIISE:Software and Applications
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    • v.35 no.4
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    • pp.207-218
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    • 2008
  • With the growth of the Internet, multimedia streaming becomes an important means to deliver video contents over the Internet and the amount of the streaming multimedia contents is also getting increased. However, it becomes difficult to guarantee the quality of service in real-time over the IP network environment with instantaneously varying bandwidth. In this paper, we propose an optimal adaptation framework for streaming contents over the Internet in the sense that the perceptual quality of the multi-angie content with multiple visual objects is maximized given the constraints such as available bandwidth and transcoding cost. In the multi-angle video service framework, the user can select his/her preferred alternate views among the given multiple video streams captured at different view angles for a same event. This enhanced experience often entails streaming problems in real-time over the network, such as instantaneous bandwidth changes in the Internet. In order to cope with this problem, we assume that multi-angle video contents are encoded at different bitrates and the appropriate video streams are then selected or transcoded for delivery to meet such bandwidth constraints. For the user selective consumption of the various bitstreams in the multi-angle video service, the bitstream in each angle can be encoded in various bitrate, and the user can select a sub-bitrstream in the given bitrstreams or transcode the corresponding content in order to deliver the optimally adapted video contents to the instantaneously changing network condition. Therefore, we define the transcoding cost which means the time taken for transcoding the video stream and formulate a unified optimization framework which maximizes the perceptual quality of the multiple video objects in the given constraints such as the transcoding cost and the network bandwidth. Finally, we present plenty of the experimental results to show the effectiveness of the proposed method.

Multi-Criteria Group Decision Making under Imprecise Preference Judgments : Using Fuzzy Logic with Linguistic Quantifier (불명료한 선호정보 하의 다기준 그룹의사결정 : Linguistic Quantifier를 통한 퍼지논리 활용)

  • Choi, Duke Hyun;Ahn, Byeong Seok;Kim, Soung Hie
    • Journal of Intelligence and Information Systems
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    • v.12 no.3
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    • pp.15-32
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    • 2006
  • The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

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Development of Road Surface Management System using Digital Imagery (수치영상을 이용한 도로 노면관리시스템 개발)

  • Seo, Dong-Ju
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.1
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    • pp.35-46
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    • 2007
  • In the study digital imagery was used to examine asphalt concrete pavements. With digitally mastered-image information that was filmed with a video camera fixed on a car travelling on road at a consistent speed, a road surface management system that can gain road surface information (Crack, Rutting, IRI) was developed using an object-oriented language "Delphi". This system was designed to improve visualized effects by animations and graphs. After analyzing the accuracy of 3-D coordinates of road surfaces that were decided using multiple image orientation and bundle adjustment method, the average of standard errors turned out to be 0.0427m in the X direction, 0.0527m in the Y direction and 0.1539m in the Z direction. As a result, it was found to be good enough to be put to practical use for maps drawn on scales below 1/1000, which are currently producted and used in our country, and GIS data. According to the analysis of the accuracy in crack width on 12 spots using a digital video camera, the standard error was found to be ${\pm}0.256mm$, which is considered as high precision. In order to get information on rutting, the physically measured cross sections of 4 spots were compared with cross sections generated from digital images. Even though a maximum error turned out to be 10.88mm, its practicality is found in work efficiency.

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A Study on SNS Reviews Analysis based on Deep Learning for User Tendency (개인 성향 추출을 위한 딥러닝 기반 SNS 리뷰 분석 방법에 관한 연구)

  • Park, Woo-Jin;Lee, Ju-Oh;Lee, Hyung-Geol;Kim, Ah-Yeon;Heo, Seung-Yeon;Ahn, Yong-Hak
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.9-17
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    • 2020
  • In this paper, we proposed an SNS review analysis method based on deep learning for user tendency. The existing SNS review analysis method has a problem that does not reflect a variety of opinions on various interests because most are processed based on the highest weight. To solve this problem, the proposed method is to extract the user's personal tendency from the SNS review for food. It performs classification using the YOLOv3 model, and after performing a sentiment analysis through the BiLSTM model, it extracts various personal tendencies through a set algorithm. Experiments showed that the performance of Top-1 accuracy 88.61% and Top-5 90.13% for the YOLOv3 model, and 90.99% accuracy for the BiLSTM model. Also, it was shown that diversity of the individual tendencies in the SNS review classification through the heat map. In the future, it is expected to extract personal tendencies from various fields and be used for customized service or marketing.

Discriminant Analysis of Human's Implicit Intent based on Eyeball Movement (안구운동 기반의 사용자 묵시적 의도 판별 분석 모델)

  • Jang, Young-Min;Mallipeddi, Rammohan;Kim, Cheol-Su;Lee, Minho
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.6
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    • pp.212-220
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    • 2013
  • Recently, there has been tremendous increase in human-computer/machine interaction system, where the goal is to provide with an appropriate service to the user at the right time with minimal human inputs for human augmented cognition system. To develop an efficient human augmented cognition system based on human computer/machine interaction, it is important to interpret the user's implicit intention, which is vague, in addition to the explicit intention. According to cognitive visual-motor theory, human eye movements and pupillary responses are rich sources of information about human intention and behavior. In this paper, we propose a novel approach for the identification of human implicit visual search intention based on eye movement pattern and pupillary analysis such as pupil size, gradient of pupil size variation, fixation length/count for the area of interest. The proposed model identifies the human's implicit intention into three types such as navigational intent generation, informational intent generation, and informational intent disappearance. Navigational intent refers to the search to find something interesting in an input scene with no specific instructions, while informational intent refers to the search to find a particular target object at a specific location in the input scene. In the present study, based on the human eye movement pattern and pupillary analysis, we used a hierarchical support vector machine which can detect the transitions between the different implicit intents - navigational intent generation to informational intent generation and informational intent disappearance.

Streptococcus thermophilus K-1 및 Lactobacillus acidophilus LB12 균주에 있어 최대 Exopolysaccharide 생산에 영향을 미치는 물리적 원인 규명을 위한 연구

  • 강현미;엄양섭;정충일
    • Proceedings of the Korean Society of Food Hygiene and Safety Conference
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    • 1999.10a
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    • pp.119-119
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    • 1999
  • EPS를 생성하는 Str. thermophilus K-1 및 Lb. acidophilus LB12를 10% 환원 탈지유에 배양하고, EPS 생산을 위한 배지로는 Elliker broth를 사용하여 20, 25 및 $37^{\circ}C$에서 72시간까지 저장하면서 12시간 간격으로 시료를 꺼내어 EPS생산량, 생균수, 산도 및 점도 등을 측정하여 EPS생산과 이들 물리저 요인들과의 상호관계를 조사하였다. Str. thermophilus K-1의 경우, $20^{\circ}C,\;37^{\circ}C$에 저장한 시료의 EPS 생산량은저장 60시간에 각각 0.358, 0.386O.D.로 최대를 나타내었으며, 저장 72시간에는 다소 감소하는 것으로 나타났다. $25^{\circ}C$에 저장한 시료는 저장 36시간부터 O.D. 0.313으로 급속히 증가하여 72시간까지 그 수준을 거의 유지하는 것으로 나타났다. Lb. acidophilus CH-2의 경우에는 25, $37^{\circ}C$에서는 EPS생산이 서서히 증가하다가, 36, 48시간에 0.775, 0.833O.D.로 각각 최대를 나타낸 후에 다시 서서히 감소하는 것으로 나타났으며, 저장 $20^{\circ}C$에서는 저장 60시간에 1.123O.D.로 EPS생산이 최대에 도달한 후 저장 72시간에는 다시 감소하는 것으로 나타났다. 이 두균주의 세 가지 배양 온도에서 EPS가 최대를 나타내는 시점은 생균수가 감소하는 시점과 일치하므로, 균주 및 배양온도에 상관없이 균성장 말기 또는 균사멸기 초기에 EPS가 가장 많이 생산됨을 알 수 있었다. 또한 점도 및 산도는 저장 온도가 높을수록, 그리고 저장 기간이 길어질수록 대체로 많이 생성되는 것으로 나타났으며, EPS생산과의 유의성도 상당히 높은 것으로 나타났다. 것들이 부딛힘이 없이 공존하고 일상의 논리가 무시된다. 부정, 의심이 없고 확실한 것이 없다. 한 대상에 가졌던 생각이 다른 대상에 옮겨간다(displacement). 한 대상이 여러 대상이 갖고 있는 의미를 함축하고 있다(condensation). 시각적인 순서가 무시된다. 마음속의 생각과 외부의 실제적인 일을 구분하지 못한다. 시간 상의 순서가 있다가 없다가 한다. 차례로 일어나야 할 일이 동시에 한꺼번에 일어난다. 대상들이 서로 비슷해지고 동시에 있을 수 없는 대상들이 함께 나타난다. 사고의 정상적인 구조가 와해된다. Matte-Blance는 무의식에서는 여러 독립된 대상들간의 구분을 없애며, 주체와 객체를 하나로 보려는 대칭화(symmetrization)의 경향이 있기 때문에 이런 변화가 생긴다고 하였다. 또 대칭화가 진행되면 무한대의 느낌을 갖게 되어, 전지(moniscience), 전능(omnipotence), 무력감(impotence), 이상화(idealization)가 나타난다. 그러나 무의식에 대칭화만 있는 것은 아니며, 의식의 사고양식인 비대칭도 어느 정도 나타나며, 대칭화의 정도에 따라, 대상들이 잘 구분되어 있는 단계, 의식수준의 감정단계, 집단 내에서의 대칭화 단계, 집단간에서의 대칭화 단계, 구분이 없어지는 단계로 구분하였다.systems. We believe that this taxonomy is a significant contribution because it adds clarity, completeness, and "global perspective" to workflow architectural discussions. The vocabulary suggested here includes workflow levels and aspects, allowing very different architectures to be discussed,

Analysis of Shadow Effect on High Resolution Satellite Image Matching in Urban Area (도심지역의 고해상도 위성영상 정합에 대한 그림자 영향 분석)

  • Yeom, Jun Ho;Han, You Kyung;Kim, Yong Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.2
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    • pp.93-98
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    • 2013
  • Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.

Evaluation of Car Prototype using CAVE-like Systems (케이브 기반 자동차 시제품 평가)

  • 고희동;안희갑;김진욱;김종국;송재복;어홍준;윤명환;우인수;박연동
    • Science of Emotion and Sensibility
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    • v.5 no.4
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    • pp.77-84
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    • 2002
  • In this paper, we propose the NAVER, a general framework for multipurpose virtual environments, and introduce the case study of evaluating car prototypes using cave-like systems. As a framework to implement variant applications in virtual environment, NAVER is extensible, reconfigurable and scalable. NAVER consists of several external modules (Render Server, Control Server and Device Server), which communicate each other to share states and user-provided data and to perform their own functions. NAVER supports its own scripting language based on XML which allows a user to define variant interactions between objects in virtual environments as well as describe the scenario of an application. We used NAVER to implement the system for evaluating car prototyes in a CAVE-like virtual environment system. The CAVE-like virtual environment system at KIST consists three side screens and a floor screen (each of them is a square with side of 2.2m), four CRT projectors displays stereoscopic images to the screens, a haptic armmaster, and a 5.1 channel sound system. The system can provide a sense of reality by displaying auditory and tactile senses as well as visual images at the same time. We evaluate car prototypes in a CAVE-like system in which a user can observe, touch and manipulate the virtual installation of car interior.

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Automation of Building Extraction and Modeling Using Airborne LiDAR Data (항공 라이다 데이터를 이용한 건물 모델링의 자동화)

  • Lim, Sae-Bom;Kim, Jung-Hyun;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.27 no.5
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    • pp.619-628
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    • 2009
  • LiDAR has capability of rapid data acquisition and provides useful information for reconstructing surface of the Earth. However, Extracting information from LiDAR data is not easy task because LiDAR data consist of irregularly distributed point clouds of 3D coordinates and lack of semantic and visual information. This thesis proposed methods for automatic extraction of buildings and 3D detail modeling using airborne LiDAR data. As for preprocessing, noise and unnecessary data were removed by iterative surface fitting and then classification of ground and non-ground data was performed by analyzing histogram. Footprints of the buildings were extracted by tracing points on the building boundaries. The refined footprints were obtained by regularization based on the building hypothesis. The accuracy of building footprints were evaluated by comparing with 1:1,000 digital vector maps. The horizontal RMSE was 0.56m for test areas. Finally, a method of 3D modeling of roof superstructure was developed. Statistical and geometric information of the LiDAR data on building roof were analyzed to segment data and to determine roof shape. The superstructures on the roof were modeled by 3D analytical functions that were derived by least square method. The accuracy of the 3D modeling was estimated using simulation data. The RMSEs were 0.91m, 1.43m, 1.85m and 1.97m for flat, sloped, arch and dome shapes, respectively. The methods developed in study show that the automation of 3D building modeling process was effectively performed.

HMM-based Intent Recognition System using 3D Image Reconstruction Data (3차원 영상복원 데이터를 이용한 HMM 기반 의도인식 시스템)

  • Ko, Kwang-Enu;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.135-140
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    • 2012
  • The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.