• Title/Summary/Keyword: 비전 기반 기술

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A Study on the Rale of counselors as clients' Transitional object (내담자의 전이대상으로 상담자의 역할 연구)

  • Yoon, Seok-Min
    • Industry Promotion Research
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    • v.5 no.3
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    • pp.53-60
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    • 2020
  • This paper describes the role of counselors' transitional object for the therapeutic activation of clients who have lost the function of selfobject based on Heinz Kohut's Self theory. In this study, it was an opportunity to confirm that human beings need self-target throughout their lives. Next, referring to the process of metamorphic internalization, infants return to reality from a fantasy world, experiencing parental limitations due to optimal frustration through self-targeting. The role of a counselor as a transfer target shall ensure that the counsellor establishes an cohesive self-identity and uses the appropriate self-target. And they should empathize with the over-the-topism and flauntism of the physician, and the counselor should be the object of idealization, giving the interviewer the opportunity to be recognized and identified. The counselor may provide the best frustration for the counsellor during the consultation process. When the counselor acknowledges his mistake, the counselor looks at the counselor realistically and builds a healthy self to achieve transformative internalization. If you form an cohesive self to a physician through counseling, you can empathize with others and form a healthy human relationship. Then you can control your emotions and have a vision. And the patient realizes that he or she has no choice but to live by having a relationship with the right person throughout his or her life.

Interaction Augmented Reality System using a Hand Motion (손동작을 이용한 상호작용 증강현실 시스템)

  • Choi, Kwang-Woon;Jung, Da-Un;Lee, Suk-Han;Choi, Jong-Soo
    • Journal of Korea Multimedia Society
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    • v.15 no.4
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    • pp.425-438
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    • 2012
  • In this paper, We propose Augmented Reality (AR) System for the interaction between user's hand motion and virtual object motion based on computer vision. The previous AR system provides inconvenience to user because the users have to control the marker and the sensor like a tracker. We solved the problem through hand motion and provide the convenience to the user. Also the motion of virtual object using a physical phenomenon gives a reality. The proposed system obtains geometrical information by the marker and hand. The system environments like virtual space of moving virtual ball and bricks are made by using the geometrical information and user's hand motion is obtained from the hand's information with extracted feature point through the taping hand. And it registers a virtual plane stably by getting movement of the feature points. The movement of the virtual ball basically is parabolic motion with a parabolic equation. When the collision occurs either the planes or the bricks, we show movement of the virtual ball with ball position and normal vector of plane and the ball position is faulted. So we showed corrected ball position through experiment. and we proved that this system can replaced the marker system to compare to jitter of augmented virtual object and progress speed with it.

Design and Implementation of Mobile Vision-based Augmented Galaga using Real Objects (실제 물체를 이용한 모바일 비전 기술 기반의 실감형 갤러그의 설계 및 구현)

  • Park, An-Jin;Yang, Jong-Yeol;Jung, Kee-Chul
    • Journal of Korea Game Society
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    • v.8 no.2
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    • pp.85-96
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    • 2008
  • Recently, research on augmented games as a new game genre has attracted a lot of attention. An augmented game overlaps virtual objects in an augmented reality(AR) environment, allowing game players to interact with the AR environment through manipulating real and virtual objects. However, it is difficult to release existing augmented games to ordinary game players, as the games generally use very expensive and inconvenient 'backpack' systems: To solve this problem, several augmented games have been proposed using mobile devices equipped with cameras, but it can be only enjoyed at a previously-installed location, as a ‘color marker' or 'pattern marker’ is used to overlap the virtual object with the real environment. Accordingly, this paper introduces an augmented game, called augmented galaga based on traditional well-known galaga, executed on mobile devices to make game players experience the game without any economic burdens. Augmented galaga uses real object in real environments, and uses scale-invariant features(SIFT), and Euclidean distance to recognize the real objects. The virtural aliens are randomly appeared around the specific objects, several specific objects are used to improve the interest aspect, andgame players attack the virtual aliens by moving the mobile devices towards specific objects and clicking a button of mobile devices. As a result, we expect that augmented galaga provides an exciting experience without any economic burdens for players based on the game paradigm, where the user interacts with both the physical world captured by a mobile camera and the virtual aliens automatically generated by a mobile devices.

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A strategic Approach for Establishing Korea's Cyber Terrorism Policy : Focusing on the UK's cyber terrorism policy (국내 사이버테러 정책수립을 위한 전략적 접근방안 : 영국의 사이버테러 정책을 중심으로)

  • Kim, Byung-Hwa
    • Korean Security Journal
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    • no.51
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    • pp.173-195
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    • 2017
  • Recently, in South Korea, security management has been strengthened, but there have been an increasing number of cases where the main infrastructure of the country is hacked in the cyber space. South Korea is equipped with sophisticated information and communication technologies, such as Internet, but is threatened by cyber terrorism of North Korea and terrorist organizations. Nevertheless, there is a limit to how to develop a policy and strategic plan for the country, which is related to domestic terrorism and lacks legal and regulatory facilities, and therefore, in this study, proposed suggestions for building adaptive and efficient policy formulation. Based on the theoretical analysis framework of the Strategic Plan for achieving the objectives of the research, we compared the UK 's security strategy with the national security policy of the domestic government. As a result, several problems were derived: First, the domestic security strategy did not take into account the external environment. Secondly, lack of coordination with domestic cyber security goals setting and strategy is causing ambiguity and confusion. Third, the detailed plan of implementation of national security in each province is designed to ensure that there is a possibility that a mixed side effect between ministries and agencies will arise. Fourth, it was found that there was a limit to prepare the evaluation standards for the evaluation and return of domestic security policies in the country. Therefore, in order to establish a policy for the response of domestic cyber terrorism, we set up a vision from long-term perspectives and concrete targets based on the strategic approach of the security policy, It is necessary to present an assignment and formulate an efficient execution plan. It is necessary to maintain and improve the domestic safeguards in order to be able to complement the problems through evaluation and feedback.

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Gaze Detection by Computing Facial and Eye Movement (얼굴 및 눈동자 움직임에 의한 시선 위치 추적)

  • 박강령
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.2
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    • pp.79-88
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    • 2004
  • Gaze detection is to locate the position on a monitor screen where a user is looking by computer vision. Gaze detection systems have numerous fields of application. They are applicable to the man-machine interface for helping the handicapped to use computers and the view control in three dimensional simulation programs. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye's movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.

Automatic Classification Technique of Offence Patterns using Neural Networks in Soccer Game (뉴럴네트워크를 이용한 축구경기 공격패턴 자동분류에 관한 연구)

  • Kim, Hyun-Sook;Yoon, Ho-Sub;Hwang, Chong-Sun;Yang, Young-Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.727-730
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    • 2001
  • 멀티미디어 환경의 급속한 발전에 의해 영상처리 기술은 인간의 인체와 관련하여 얼굴인식, 제스처 인식에 관한 응용과 더불어 스포츠 관련분야로 깊숙히 정착하고 있다. 그러나 입력영상으로부터 움직이고 있는 선수들의 동작을 추출 및 추적하는 일은 컴퓨터비전 연구의 난 문제 중의 하나로 알려져 있다. 이러한 축구경기의 TV 중계에 있어서 하이라이트 장면의 자동추출(자동색인)은 그 경기의 가장 집약적인 표현이며, 축구경기 전체를 한 눈에 파악할 수 있도록 해주는 요약(summary)이자 intensive actions이고 경기의 진수이다. 따라서 축구경기와 같이 비교적 기 시간(대체로 1시간 30분) 동안 다수의 선수(양 팀 합해서 22명)들이 서로 복잡하게 뒤얽히면서 진행하는 경기의 하이라이트 장면을 효과적으로 포착하여 표현해 줄 수 있다면 TV를 통해서 경기를 관람하는 시청자들에게는 경기의 진행상황을 한 눈에 효과적으로 파악할 수 있게 해주어 흥미진진한 경기관람을 할 수 있게 해주고, 경기의 진행자들(감독, 코치, 선수 등)에게는 고차원적이고 과학적인 정보를 효과적으로 제공함으로써 한층 진보된 경기기법을 개발하고 과학적인 경기전략을 세울 수 있게 해준다. 본 논문은 이상과 같이 팀 스포츠(Team Spots)의 일종인 축구경기 하이라이트 장면의 자동색인을 위해 뉴럴네트워크 기법을 이용하여 그룹 포메이션(Group Formation) 중의 공격패턴 자동분류 기법을 개발하고 이를 검증하였다. 본 연구에서는 축구경기장 내의 빈번하게 변화하는 장면들을 자동으로 분할하여 대표 프레임을 선정하고, 대표 프레임 상에서 선수들의 위치정보와 공의 위치정보 등을 기초로 하여 경기 중에 이루어지는 선수들의 그룹 포메이션을 추적하여 그룹행동(group behavior)을 분석하고, 뉴럴네트워크의 BP(Back-Propagation) 알고리즘을 사용하여 축구경기 공격패턴을 자동으로 인식 및 분류함으로써 축구경기 하이라이트 장면의 자동추출을 위한 기반을 마련하였다. 본 연구의 실험에는 '98 프랑스 월드컵 축구경기의 다양한 공격패턴에 대한 비디오 영상에서 각각 좌측공격 60개, 우측공격 74개, 중앙공격 72개, 코너킥 39개, 프리킥 52개의 총 297개의 데이터를 추출하여 사용하였다. 실험과는 좌측공격 91.7%, 우측공격 100%, 중앙공격 87.5%, 코너킥 97.4%, 프리킥 75%로서 매우 양호한 인식율을 보였다.

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Model-Based Plane Detection in Disparity Space Using Surface Partitioning (표면분할을 이용한 시차공간상에서의 모델 기반 평면검출)

  • Ha, Hong-joon;Lee, Chang-hun
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.10
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    • pp.465-472
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    • 2015
  • We propose a novel plane detection in disparity space and evaluate its performance. Our method simplifies and makes scenes in disparity space easily dealt with by approximating various surfaces as planes. Moreover, the approximated planes can be represented in the same size as in the real world, and can be employed for obstacle detection and camera pose estimation. Using a stereo matching technique, our method first creates a disparity image which consists of binocular disparity values at xy-coordinates in the image. Slants of disparity values are estimated by exploiting a line simplification algorithm which allows our method to reflect global changes against x or y axis. According to pairs of x and y slants, we label the disparity image. 4-connected disparities with the same label are grouped, on which least squared model estimates plane parameters. N plane models with the largest group of disparity values which satisfy their plane parameters are chosen. We quantitatively and qualitatively evaluate our plane detection. The result shows 97.9%와 86.6% of quality in our experiment respectively on cones and cylinders. Proposed method excellently extracts planes from Middlebury and KITTI dataset which are typically used for evaluation of stereo matching algorithms.

U-Net Cloud Detection for the SPARCS Cloud Dataset from Landsat 8 Images (Landsat 8 기반 SPARCS 데이터셋을 이용한 U-Net 구름탐지)

  • Kang, Jonggu;Kim, Geunah;Jeong, Yemin;Kim, Seoyeon;Youn, Youjeong;Cho, Soobin;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1149-1161
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    • 2021
  • With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.

Comparison of Artificial Intelligence Multitask Performance using Object Detection and Foreground Image (물체탐색과 전경영상을 이용한 인공지능 멀티태스크 성능 비교)

  • Jeong, Min Hyuk;Kim, Sang-Kyun;Lee, Jin Young;Choo, Hyon-Gon;Lee, HeeKyung;Cheong, Won-Sik
    • Journal of Broadcast Engineering
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    • v.27 no.3
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    • pp.308-317
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    • 2022
  • Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

A Deep Learning Method for Cost-Effective Feed Weight Prediction of Automatic Feeder for Companion Animals (반려동물용 자동 사료급식기의 비용효율적 사료 중량 예측을 위한 딥러닝 방법)

  • Kim, Hoejung;Jeon, Yejin;Yi, Seunghyun;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.263-278
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    • 2022
  • With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.