• Title/Summary/Keyword: Distance Learning System

Search Result 398, Processing Time 0.029 seconds

Face Recognition Research Based on Multi-Layers Residual Unit CNN Model

  • Zhang, Ruyang;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
    • /
    • v.25 no.11
    • /
    • pp.1582-1590
    • /
    • 2022
  • Due to the situation of the widespread of the coronavirus, which causes the problem of lack of face image data occluded by masks at recent time, in order to solve the related problems, this paper proposes a method to generate face images with masks using a combination of generative adversarial networks and spatial transformation networks based on CNN model. The system we proposed in this paper is based on the GAN, combined with multi-scale convolution kernels to extract features at different details of the human face images, and used Wasserstein divergence as the measure of the distance between real samples and synthetic samples in order to optimize Generator performance. Experiments show that the proposed method can effectively put masks on face images with high efficiency and fast reaction time and the synthesized human face images are pretty natural and real.

Tracking Players in Broadcast Sports

  • Sudeep, Kandregula Manikanta;Amarnath, Voddapally;Pamaar, Angoth Rahul;De, Kanjar;Saini, Rajkumar;Roy, Partha Pratim
    • Journal of Multimedia Information System
    • /
    • v.5 no.4
    • /
    • pp.257-264
    • /
    • 2018
  • Over the years application of computer vision techniques in sports videos for analysis have garnered interest among researchers. Videos of sports games like basketball, football are available in plenty due to heavy popularity and coverage. The goal of the researchers is to extract information from sports videos for analytics which requires the tracking of the players. In this paper, we explore use of deep learning networks for player spotting and propose an algorithm for tracking using Kalman filters. We also propose an algorithm for finding distance covered by players. Experiments on sports video datasets have shown promising results when compared with standard techniques like mean shift filters.

Technologies Of Educational Activity Development: Theoretical Fundamentals

  • Kravchuk, Nadiia;Kinakh, Nelia;Bortniuk, Tetiana;Fedosenko, Karina;Burlaka, Anna
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.11
    • /
    • pp.177-180
    • /
    • 2021
  • The theoretical and methodological provisions that allow to systematically and comprehensively study the postgraduate pedagogical education of teachers; the essence and features of postgraduate pedagogical education of teachers of diverse training institutions, providing professional and pedagogical training of this category of pedagogical personnel, have been determined; regularities, principles and conditions for the implementation of promising directions of development of the system of postgraduate pedagogical education for teachers of diverse training have been developed; developed technological support for the development of postgraduate pedagogical education for teachers of multidisciplinary training; identified and substantiated promising directions for the development of postgraduate pedagogical education for teachers of multidisciplinary training in vocational education, due to the modernization.

Song Player by Distance Measurement from Face (얼굴에서 거리 측정에 의한 노래 플레이어)

  • Shin, Seong-Yoon;Lee, Min-Hye;Shin, Kwang-Seong;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2022.05a
    • /
    • pp.667-669
    • /
    • 2022
  • In this paper, Face Song Player, which is a system that recognizes the facial expression of an individual and plays music that is appropriate for such person, is presented. It studies information on the facial contour lines and extracts an average, and acquires the facial shape information. MUCT DB was used as the DB for learning. For the recognition of facial expression, an algorithm was designed by using the differences in the characteristics of each of the expressions on the basis of expressionless images.

  • PDF

Development of an algorithm for solving correspondence problem in stereo vision (스테레오 비젼에서 대응문제 해결을 위한 알고리즘의 개발)

  • Im, Hyuck-Jin;Gweon, Dae-Gab
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.10 no.1
    • /
    • pp.77-88
    • /
    • 1993
  • In this paper, we propose a stereo vision system to solve correspondence problem with large disparity and sudden change in environment which result from small distance between camera and working objects. First of all, a specific feature is divided by predfined elementary feature. And then these are combined to obtain coded data for solving correspondence problem. We use Neural Network to extract elementary features from specific feature and to have adaptability to noise and some change of the shape. Fourier transformation and Log-polar mapping are used for obtaining appropriate Neural Network input data which has a shift, scale, and rotation invariability. Finally, we use associative memory to obtain coded data of the specific feature from the combination of elementary features. In spite of specific feature with some variation in shapes, we could obtain satisfactory 3-dimensional data from corresponded codes.

  • PDF

Automatic Attendance Check System Using Face Recognition In A Masked Environment (마스크를 착용한 환경에서 얼굴 인식을 활용한 자동 출석체크 시스템)

  • Kim, Young-Kook;Lim, Chae-Hyun;Son, Min-Ji;Kim, Myung-Ho
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2020.07a
    • /
    • pp.23-26
    • /
    • 2020
  • 본 논문에서는 CCTV를 통해 얻은 영상에서 얼굴을 인식하여 자동으로 출석 여부를 체크하는 시스템을 소개한다. 이 시스템은 CNN을 바탕으로 RetinaFace 모델을 사용하여 얼굴을 탐지하고, 탐지된 얼굴을 ArcFace 모델로 R512의 목표 공간으로 임베딩한다. 기존 데이터베이스에 등록된 얼굴과 CCTV를 통해 얻은 얼굴들의 임베딩 벡터 사이의 Angular Cosine Distance를 측정하여 동일 인물인지 판단하는 매칭 알고리즘을 제안한다. 실험을 통해 두 모델을 동시에 사용할 최적의 환경을 파악하고, 마스크 착용으로 얼굴의 하단부가 가려지는 폐색 문제에 더욱 효과적으로 대응하여 매칭 성능을 높이는 방법을 제안한다.

  • PDF

Study of Target Pose Estimation System: Distance Measurement Based Deep Learning Using Single Camera (딥러닝 단일카메라 거리 측정 기술 활용 구조대상자 위치추정시스템 연구)

  • Do-Yun Kim;Jong-In Choi ;Seo-Won Park ;Kwang-Young Park
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2023.05a
    • /
    • pp.560-561
    • /
    • 2023
  • 지진, 대형화재와 같은 많은 재해의 발생으로 인해 재난 안전 분야에 관심이 증가하고 있으며, 재난재해 시 신속하고 안전한 구조는 생존율에 영향을 준다. 기존 연구에서는 다양한 센서와 멀티카메라를 이용한 위치 추정 연구는 있으나, 가장 많이 설치된 단일카메라 기반의 위치 추정연구는 부족한 상태이다. 본 논문에서 단일카메라를 활용한 딥러닝 객체탐지와 거리측정 알고리즘을 이용하여 인명구조를 위한 구조대상자 위치추정시스템을 제안한다. 딥러닝을 활용한 객체탐지 기술을 이용하여 단일카메라 영상 내 객체와 해상도에 따른 바운딩 박스의 너비를 활용한 거리 계산식으로 거리를 추정하고, 객체의 위치좌표를 제공하여 신속한 재난 구조에 도움이 되는 시스템을 제안한다.

Graph Learning System for Analyzing Bias among News Using Keyword Distance Model (주제어 문장거리를 이용한 뉴스 편향성 분석 그래프 학습)

  • Cho Chanwoo;Cho Chanhyung
    • Annual Conference on Human and Language Technology
    • /
    • 2023.10a
    • /
    • pp.533-538
    • /
    • 2023
  • 문서에서 저자의 의도와 주제, 그 안에 포함된 감성을 분석하는 것은 자연어 연구의 핵심적인 주제이다. 이와 유사하게 특정 글에 포함된 정치적 문화적 편향을 분석하는 것 역시 매우 의미 있는 연구주제이다. 우리는 최근 발생한 한 사건에 대하여 여러 신문사와 해당 신문사에서 생산한 기사를 중심으로 해당 글의 정치적 편향을 정량화 하는 방법을 제시한다. 그 방법은 선택된 주제어들의 문장 공간에서의 거리를 중심으로 그래프를 생성하고, 생성된 그래프의 기계학습을 통하여 편향과 특징을 분석하였다. 그리고 그 그래프들의 시간적 변화를 추적하여 특정 신문사에서 특정 사건에 대한 입장이 시간적으로 어떻게 변화하였는지를 동적으로 보여주는 그래프 애니메이션 시스템을 개발하였다. 실험을 위하여 최근 이슈에 대하여 12개의 신문사에서 약 2000여 개의 기사를 수집하였다. 그 결과, 약 82%의 정확도로 일반적으로 알려진 정치적 편향을 예측할 수 있었다. 또한, 학습 데이터에 쓰이지 않은 신문기사를 활용하여도 같은 정도의 정확도를 보임을 알 수 있었다. 우리는 이를 통하여 신문기사에서의 정치적 편향은 작성자나 신문사의 특성이 아니라 주제어들의 문장 공간에서의 거리 관계로 특성화할 수 있음을 보였다. 할 수 있다.

  • PDF

Reliability measure improvement of Phoneme character extract In Out-of-Vocabulary Rejection Algorithm (미등록어 거절 알고리즘에서 음소 특성 추출의 신뢰도 측정 개선)

  • Oh, Sang-Yeob
    • Journal of Digital Convergence
    • /
    • v.10 no.6
    • /
    • pp.219-224
    • /
    • 2012
  • In the communication mobile terminal, Vocabulary recognition system has low recognition rates, because this problems are due to phoneme feature extract from inaccurate vocabulary. Therefore they are not recognize the phoneme and similar phoneme misunderstanding error. To solve this problem, this paper propose the system model, which based on the two step process. First, input phoneme is represent by number which measure the distance of phonemes through phoneme likelihood process. next step is recognize the result through the reliability measure. By this process, we minimize the phoneme misunderstanding error caused by inaccurate vocabulary and perform error correction rate for error provrd vocabulary using phoneme likelihood and reliability. System performance comparison as a result of recognition improve represent 2.7% by method using error pattern learning and semantic pattern.

Emotion Recognition and Expression System of Robot Based on 2D Facial Image (2D 얼굴 영상을 이용한 로봇의 감정인식 및 표현시스템)

  • Lee, Dong-Hoon;Sim, Kwee-Bo
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.13 no.4
    • /
    • pp.371-376
    • /
    • 2007
  • This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.