• Title/Summary/Keyword: real self-image

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Compact near-eye display for firefighter's self-contained breathing apparatus

  • Ungyeon Yang
    • ETRI Journal
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    • v.45 no.6
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    • pp.1046-1055
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    • 2023
  • We introduce a display for virtual-reality (VR) fire training. Firefighters prefer to wear and operate a real breathing apparatus while experiencing full visual immersion in a VR fire space. Thus, we used a thin head-mounted display (HMD) with a light field and folded optical system, aiming to both minimize the volume for integration in front of the face into a breathing apparatus and maintain adequate visibility, including a wide viewing angle and resolution similar to that of commercial displays. We developed the optical system testing modules and prototypes of the integrated breathing apparatus. Through iterative testing, the thickness of the output optical module in front of the eyes was reduced from 50 mm to 60 mm to less than 20 mm while maintaining a viewing angle of 103°. In addition, the resolution and image quality degradation of the light field in the display was mitigated. Hence, we obtained a display with a structure consistent with the needs of firefighters in the field. In future work, we will conduct user evaluation regarding fire scene reproducibility by combining immersive VR fire training and real firefighting equipment.

A Study on the Creation of Digital Self-portrait with Intertextuality (상호텍스트성을 활용한 디지털 자화상 창작)

  • Lim, Sooyeon
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.427-434
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    • 2022
  • The purpose of this study is to create a self-portrait that provides an immersive experience that immerses the viewer into the problem of self-awareness. We propose a method to implement an interactive self-portrait by using audio and image information obtained from viewers. The viewer's voice information is converted into text and visualized. In this case, the viewer's face image is used as pixel information composing the text. Text is the result of a mixture of one's own emotions, imaginations, and intentions based on personal experiences and memories. People have different interpretations of certain texts in different ways.The proposed digital self-portrait not only reproduces the viewer's self-consciousness in the inner aspect by utilizing the intertextuality of the text, but also expands the meanings inherent in the text. Intertextuality in a broad sense refers to the totality of all knowledge that occurs between text and text, and between subject and subject. Therefore, the self-portrait expressed in text expands and derives various relationships between the viewer and the text, the viewer and the viewer, and the text and the text. In addition, this study shows that the proposed self-portrait can confirm the formativeness of text and re-create spatial and temporality in the external aspect. This dynamic self-portrait reflects the interests of viewers in real time, and has the characteristic of being updated and created.

Container Image Recognition using Fuzzy-based Noise Removal Method and ART2-based Self-Organizing Supervised Learning Algorithm (퍼지 기반 잡음 제거 방법과 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 컨테이너 인식 시스템)

  • Kim, Kwang-Baek;Heo, Gyeong-Yong;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.7
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    • pp.1380-1386
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    • 2007
  • This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is blacker white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tacking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm. Experiments using real images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed.

Survey on Body Image Perception, Dietary Habits and Nutrient Intakes according to Interest Level in Health of Female University Students in Gyeongnam Area (경남지역 일부 여대생의 건강관심도에 따른 체형인식, 식생활습관과 영양소 섭취 실태 조사)

  • Seo, Eun-Hee
    • The Korean Journal of Food And Nutrition
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    • v.28 no.2
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    • pp.281-294
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    • 2015
  • This study was conducted using a self boarding questionnaire survey to investigate body image perception, dietary habits and nutrient intakes according to interest level in health of female university students in Masan area (n=302). The subjects were divided into 2 groups according to interest level in health ('High' group, n=101, 'Low' group, n=201). Body image according to BMI was significantly different regardless of interest level in health (p<0.001). The answer percentage indicated that the purpose of weight control is health, regular use of the scale, and regular exercise were significantly higher in the high group (p<0.05). Nutrient knowledge score (p<0.01) and food frequency score (p<0.001) were significantly higher in the high group (p<0.01). There were no significant differences in nutrient intake, but intake, NAR and INQ of vitamin C were significantly higher in the high group (p<0.001). Nutrition knowledge score (p<0.01), food intake frequency score (p<0.01), and INQ and NAR of vitamin C (p<0.01) were positively correlated with the interest level in health. These results will be useful as a basis for the development of effective nutrition education programs in order to increase interest level in health and apply well in real life what have learned through the correct nutrition knowledge.

DiLO: Direct light detection and ranging odometry based on spherical range images for autonomous driving

  • Han, Seung-Jun;Kang, Jungyu;Min, Kyoung-Wook;Choi, Jungdan
    • ETRI Journal
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    • v.43 no.4
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    • pp.603-616
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    • 2021
  • Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

A Attendance-Absence Checking System using the Self-organizing Face Recognition (자기조직형 얼굴 인식에 의한 학생 출결 관리 시스템)

  • Lee, Woo-Beom
    • The Journal of the Korea Contents Association
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    • v.10 no.3
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    • pp.72-79
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    • 2010
  • A EAARS(Electronic Attendance-Absence Recording System) is the important LSS(Learning Support System) for blending a on-line learning in the face-to-face classroom. However, the EAARS based on the smart card can not identify a real owner of the checked card. Therefore, we develop the CS(Client-Sever) system that manages the attendance-absence checking automatically, which is used the self-organizing neural network for the face recognition. A client system creates the ID file by extracting the face feature, a server system analyzes the ID file sent from client system, and performs a student identification by using the Recognized weight file saved in Database. As a result, The proposed CS EAARS shows the 92% efficiency in the CS environment that includes the various face image database of the real classroom.

Intelligent Hybrid Fusion Algorithm with Vision Patterns for Generation of Precise Digital Road Maps in Self-driving Vehicles

  • Jung, Juho;Park, Manbok;Cho, Kuk;Mun, Cheol;Ahn, Junho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.10
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    • pp.3955-3971
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    • 2020
  • Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

A Real time Image Resizer with Enhanced Scaling Precision and Self Parameter Calculation (강화된 스케일링 정밀도와 자체 파라미터 계산 기능을 가진 실시간 이미지 크기 조절기)

  • Kim, Kihyun;Ryoo, Kwangki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.99-102
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    • 2012
  • An image scaler is a IP used in a image processing block of display devices to adjust image size. Proposed image scaler adopts line memories instead of a conventional method using a frame memory. This method reduced hardware resources and enhanced data precision by using shift operations that number is multiplied by $2^m$ and divided again at final stage for scaling. Also image scaler increased efficiency of IP by using serial divider to calculate parameters by itself. Parameters used in image scaling is automatically produced by it. Suggested methods are designed by Verilog HDL and implemented with Xilinx Vertex-4 XC4LX80 and ASIC using TSMC 0.18um process.

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Video Art and Media Environment in City Space (도시 공간에서의 비디오 아트와 미디어 환경에의 재고)

  • Sohn, Young-Sil
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.196-206
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    • 2011
  • The development of projection technology produces series of discussions associated to various form of visual immersing possibilities by the way of projecting image directly to the obscure surface surrounded us. Besides, the significance can be found in terms of that this kind of image projection offers chance to citizens to enjoy high standard images and makes people consider media environment of city. Video art as the digital technology grafts penetrates formative space of city by projecting images. The certain thing about questions how the media has status in city is that media is now not existing for self neither for abstractly and virtual reality is existing in the general appearance of metropolis. This paper treats media environment of city and the meaning of image projection as from of video art in the city. It accesses about the meaning of video form visual art in big city- new reality, the virtual and the real, immersion and interactivity. And media reality of metropolis defines that there is not one major discourse in the gigantic text -metropolis rather they are different discourses each other simultaneously compatible in the gigantic text -metropolis and in fact, they affect each other and interact.

The Embodiment of the Real-Time Face Recognition System Using PCA-based LDA Mixture Algorithm (PCA 기반 LDA 혼합 알고리즘을 이용한 실시간 얼굴인식 시스템 구현)

  • 장혜경;오선문;강대성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.45-50
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    • 2004
  • In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.