• Title/Summary/Keyword: 카메라 기반 인식

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Enterprise Human Resource Management using Hybrid Recognition Technique (하이브리드 인식 기술을 이용한 전사적 인적자원관리)

  • Han, Jung-Soo;Lee, Jeong-Heon;Kim, Gui-Jung
    • Journal of Digital Convergence
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    • v.10 no.10
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    • pp.333-338
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    • 2012
  • Human resource management is bringing the various changes with the IT technology. In particular, if HRM is non-scientific method such as group management, physical plant, working hours constraints, personal contacts, etc, the current enterprise human resources management(e-HRM) appeared in the individual dimension management, virtual workspace (for example: smart work center, home work, etc.), working time flexibility and elasticity, computer-based statistical data and the scientific method of analysis and management has been a big difference in the sense. Therefore, depending on changes in the environment, companies have introduced a variety of techniques as RFID card, fingerprint time & attendance systems in order to build more efficient and strategic human resource management system. In this paper, time and attendance, access control management system was developed using multi camera for 2D and 3D face recognition technology-based for efficient enterprise human resource management. We had an issue with existing 2D-style face-recognition technology for lighting and the attitude, and got more than 90% recognition rate against the poor readability. In addition, 3D face recognition has computational complexities, so we could improve hybrid video recognition and the speed using 3D and 2D in parallel.

Development of Virtual Makeup Tool based on Mobile Augmented Reality

  • Song, Mi-Young;Kim, Young-Sun
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.127-133
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    • 2021
  • In this study, an augmented reality-based make-up tool was built to analyze the user's face shape based on face-type reference model data and to provide virtual makeup by providing face-type makeup. To analyze the face shape, first recognize the face from the image captured by the camera, then extract the features of the face contour area and use them as analysis properties. Next, the feature points of the extracted face contour area are normalized to compare with the contour area characteristics of each face reference model data. Face shape is predicted and analyzed using the distance difference between the feature points of the normalized contour area and the feature points of the each face-type reference model data. In augmented reality-based virtual makeup, in the image input from the camera, the face is recognized in real time to extract the features of each area of the face. Through the face-type analysis process, you can check the results of virtual makeup by providing makeup that matches the analyzed face shape. Through the proposed system, We expect cosmetics consumers to check the makeup design that suits them and have a convenient and impact on their decision to purchase cosmetics. It will also help you create an attractive self-image by applying facial makeup to your virtual self.

Class 1·3 Vehicle Classification Using Deep Learning and Thermal Image (열화상 카메라를 활용한 딥러닝 기반의 1·3종 차량 분류)

  • Jung, Yoo Seok;Jung, Do Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.96-106
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    • 2020
  • To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

A Study on the Development of a Korean Manual Alphabet Learning Game with Avatar (아바타를 내장한 한글 지문자 학습 게임 개발에 관한 연구)

  • Oh, Youung-Joon;Jung, Kee-Chul
    • Journal of Korea Game Society
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    • v.9 no.4
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    • pp.67-80
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    • 2009
  • In this paper, we described the development of a Korean Manual Alphabet (KMA) learning game with avatar. KMA letters correspond to the vocabulary of Korean Sign Language (KSL) when spelling a word. Each KMA letter corresponds to a letter of the Korean Alphabet (KA) and KA is represented as hand shapes by sign language user. We developed a KMA learning game for a beginner to learn KMA letters from sign language avatar and practice KMA presentation easily. The system composed of sign language teacher avatar GUI popup window based on OpenGL, KMA letter recognition module, KA letter raining game module and USB camera. A user learns a KMA letter with expressing KA syllabic from avatar and inputs a KMA letter to the system using USB camera. We evaluated the efficiency of the developed system through the verification of users.

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Object Position Estimation and Optimal Moving Planning of Mobile Manipulator based on Active Camera (능동카메라기반 이동매니퓰레이터의 물체위치추정 및 최적동작계획)

  • Jin, Tae-Seok;Lee, Jang-Myung
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.42 no.5 s.305
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    • pp.1-12
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    • 2005
  • A Mobile manipulator - a serial connection of a mobile robot and a task robot - is a very useful system to achieve various tasks in dangerous environment. because it has the higher performance than a fixed base manipulator in regard to the size of it's operational workspace. Unfortunately the use of a mobile robot introduces non-holonomic constraints, and the combination of a mobile robot and a manipulator generally introduces kinematic redundancy. In this paper, first a method for estimating the position of object at the cartesian coordinate system acquired by using the geometrical relationship between the image captured by 2-DOF active camera mounted on mobile robot and real object is proposed. Second, we propose a method to determine a optimal path between current the position of mobile manipulator whose mobile robot is non-holonomic and the position of object estimated by image information through the global displacement of the system in a symbolic way, using homogenous matrices. Then, we compute the corresponding joint parameters to make the desired displacement coincide with the computed symbolic displacement and object is captured through the control of a manipulator. The effectiveness of proposed method is demonstrated by the simulation and real experiment using the mobile manipulator.

People Counting System by Facial Age Group (얼굴 나이 그룹별 피플 카운팅 시스템)

  • Ko, Ginam;Lee, YongSub;Moon, Nammee
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.2
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    • pp.69-75
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    • 2014
  • Existing People Counting System using a single overhead mounted camera has limitation in object recognition and counting in various environments. Those limitations are attributable to overlapping, occlusion and external factors, such as over-sized belongings and dramatic light change. Thus, this paper proposes the new concept of People Counting System by Facial Age Group using two depth cameras, at overhead and frontal viewpoints, in order to improve object recognition accuracy and robust people counting to external factors. The proposed system is counting the pedestrians by five process such as overhead image processing, frontal image processing, identical object recognition, facial age group classification and in-coming/out-going counting. The proposed system developed by C++, OpenCV and Kinect SDK, and it target group of 40 people(10 people by each age group) was setup for People Counting and Facial Age Group classification performance evaluation. The experimental results indicated approximately 98% accuracy in People Counting and 74.23% accuracy in the Facial Age Group classification.

Development of a Cause Analysis Program to Risky Driving with Vision System (Vision 시스템을 이용한 위험운전 원인 분석 프로그램 개발에 관한 연구)

  • Oh, Ju-Taek;Lee, Sang-Yong
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.149-161
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    • 2009
  • Electronic control systems of vehicle are rapidly developed to keep balance of a driver`s safety and the legal, social needs. The driver assistance systems are putted into practical use according to the cost drop in hardware and highly efficient sensor, etc. This study has developed a lane and vehicle detection program using CCD camera. The Risky Driving Analysis Program based on vision systems is developed by combining a risky driving detection algorithm formed in previous study with lane and vehicle detection program suggested in this study. Risky driving detection programs developed in this study with information coming from the vehicle moving data and lane data are useful in efficiently analyzing the cause and effect of risky driving behavior.

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Development of Fire Detection Algorithm using Intelligent context-aware sensor (상황인지 센서를 활용한 지능형 화재감지 알고리즘 설계 및 구현)

  • Kim, Hyeng-jun;Shin, Gyu-young;Oh, Young-jun;Lee, Kang-whan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.93-96
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    • 2015
  • In this paper, we introduce a fire detection system using context-aware sensor. In existing weather and based on vision sensor of fire detection system case, acquired image through sensor of camera is extracting features about fire range as processing to convert HSI(Hue, Saturation, Intensity) model HSI which is color space can have durability in illumination changes. However, in this case, until a fire occurs wide range of sensing a fire in a single camera sensor, it is difficult to detect the occurrence of a fire. Additionally, the fire detection in complex situations as well as difficult to separate continuous boundary is set for the required area is difficult. In this paper, we propose an algorithm for real-time by using a temperature sensor, humidity, Co2, the flame presence information acquired and comparing the data based on multiple conditions, analyze and determine the weighting according to fire it. In addition, it is possible to differential management to intensive fire detection is required zone dividing the state of fire.

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Realtime 3D Stereoscopic Image based on Single Camera with Marker Recognition (마커 인식을 이용한 싱글카메라 기반의 실시간 3D 입체영상)

  • Hyun, Hye-Jung;Park, Jun-Hyoung;Ko, Il-Ju
    • The Journal of the Korea Contents Association
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    • v.11 no.1
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    • pp.92-101
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    • 2011
  • However, in order to create a stereoscopic 3D image, independently, it is required to spend expensive manufacturing costs and to have special techniques. As 3D display devices have been generalized, there is an increasing need for implementing a stereoscopic 3D image without a burden of expensive costs. This paper proposes some methods to implement stereoscopic 3D images easily by utilizing a marker tracking technology using a single camera. In addition, the study made it possible for the resolution of an image to be adjustable dynamically. This paper will be committed to the promotion of the field of UCC (User Created Contents) using stereoscopic 3D images by attracting the active participation of general users in the field of the implementation of stereoscopic 3D images.

The Implementation of User Image Recognition based on Embedded Linux (임베디드 리눅스 기반의 사용자 영상인식시스템 구현)

  • Park, Chang-Hee;Kang, Jin-Suk;Ko, Suk-Man;Kim, Jang-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.2
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    • pp.239-247
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    • 2007
  • In this paper, we propose a system that the Linux is ported in embedded system with peripheral devices of CIS(CMOS Image Sensor) and GPS module. The system acquires GGA sentence from GPS module by recognizing camera and GPS is used module in Linux kernel. And then the received location information is used to include still image acquired through CIS According to this paper, We compose hardware for embedded system, attach board (including camera), port Linux BootLoader and Kernel. And. then we realize that it insert kernel in CIS control device driver and GPS module device driver.