• Title/Summary/Keyword: Face Detecting

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A Study on a Method for Detecting Leak Holes in Respirators Using IoT Sensors

  • Woochang Shin
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.378-385
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    • 2023
  • The importance of wearing respiratory protective equipment has been highlighted even more during the COVID-19 pandemic. Even if the suitability of respiratory protection has been confirmed through testing in a laboratory environment, there remains the potential for leakage points in the respirators due to improper application by the wearer, damage to the equipment, or sudden movements in real working conditions. In this paper, we propose a method to detect the occurrence of leak holes by measuring the pressure changes inside the mask according to the wearer's breathing activity by attaching an IoT sensor to a full-face respirator. We designed 9 experimental scenarios by adjusting the degree of leak holes of the respirator and the breathing cycle time, and acquired respiratory data for the wearer of the respirator accordingly. Additionally, we analyzed the respiratory data to identify the duration and pressure change range for each breath, utilizing this data to train a neural network model for detecting leak holes in the respirator. The experimental results applying the developed neural network model showed a sensitivity of 100%, specificity of 94.29%, and accuracy of 97.53%. We conclude that the effective detection of leak holes can be achieved by incorporating affordable, small-sized IoT sensors into respiratory protective equipment.

Implementation of apparatus for detecting Ringer's solution exhaustion using electrostatic capacitance variation (정전용량변화를 이용한 링거액소진감지장치의 구현)

  • Kim, Cheong-Worl
    • Journal of Sensor Science and Technology
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    • v.19 no.1
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    • pp.1-7
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    • 2010
  • Electrostatic capacitance measurement method in a fine hose was proposed, in which two ring-type electrodes were disposed on the hose in the direction of fluid flow instead of the conventional face-to-face electrodes. With the proposed electrode structure, we realized a Ringer's solution exhaustion detector for an IV(invasive vein) injection set. On a 4 mm-diameter hose of IV set, we disposed two ring-type electrodes of 10 mm width at a distance of 5 mm each other and obtained 0.72 pF and 2.51 pF for air and 10 % dextrose Ringer's solution in the hose, respectively. The capacitance between the two electrodes varied with the hose-wraparound coverage of electrode as well as the width of electrode and the distance between the electrodes. For hose-wraparound electrode coverage of 75 %, the capacitance varied from 0.62 pF to 1.98 pF with the Ringer's solution level between the two electrodes. A charge amplifier converted the capacitance. variation into electric signal and a comparator was used to detect whether Ringer's solution was exhausted or not. The result was delivered to a host using a RF transmitter with 320 MHz carrier frequency.

Human Detection in the Images of a Single Camera for a Corridor Navigation Robot (복도 주행 로봇을 위한 단일 카메라 영상에서의 사람 검출)

  • Kim, Jeongdae;Do, Yongtae
    • The Journal of Korea Robotics Society
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    • v.8 no.4
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    • pp.238-246
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    • 2013
  • In this paper, a robot vision technique is presented to detect obstacles, particularly approaching humans, in the images acquired by a mobile robot that autonomously navigates in a narrow building corridor. A single low-cost color camera is attached to the robot, and a trapezoidal area is set as a region of interest (ROI) in front of the robot in the camera image. The lower parts of a human such as feet and legs are first detected in the ROI from their appearances in real time as the distance between the robot and the human becomes smaller. Then, the human detection is confirmed by detecting his/her face within a small search region specified above the part detected in the trapezoidal ROI. To increase the credibility of detection, a final decision about human detection is made when a face is detected in two consecutive image frames. We tested the proposed method using images of various people in corridor scenes, and could get promising results. This method can be used for a vision-guided mobile robot to make a detour for avoiding collision with a human during its indoor navigation.

Development of Web-cam Game using Hand and Face Skin Color (손과 얼굴의 피부색을 이용한 웹캠 게임 개발)

  • Oh, Chi-Min;Aurrahman, Dhi;Islam, Md. Zahidul;Kim, Hyung-Gwan;Lee, Chil-Woo
    • 한국HCI학회:학술대회논문집
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    • 2008.02b
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    • pp.60-63
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    • 2008
  • The sony Eytoy is developed on Playstation 2 using webcam for detecting human. A user see his appearance in television and become real gamer in the game. It is very different interface compared with ordinary video game which uses joystick. Although Eyetoy already was made for commercial products but the interface method still is interesting and can be added with many techniques like gesture recognition. In this paper, we have developed game interface with image processing for human hand and face detection and with game graphic module. And we realize one example game for busting balloons and demonstrated the game interface abilities. We will open this project for other developers and will be developed very much.

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Hand Raising Pose Detection in the Images of a Single Camera for Mobile Robot (주행 로봇을 위한 단일 카메라 영상에서 손든 자세 검출 알고리즘)

  • Kwon, Gi-Il
    • The Journal of Korea Robotics Society
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    • v.10 no.4
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    • pp.223-229
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    • 2015
  • This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

Recognizing Human Facial Expressions and Gesture from Image Sequence (연속 영상에서의 얼굴표정 및 제스처 인식)

  • 한영환;홍승홍
    • Journal of Biomedical Engineering Research
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    • v.20 no.4
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    • pp.419-425
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    • 1999
  • In this paper, we present an algorithm of real time facial expression and gesture recognition for image sequence on the gray level. A mixture algorithm of a template matching and knowledge based geometrical consideration of a face were adapted to locate the face area in input image. And optical flow method applied on the area to recognize facial expressions. Also, we suggest hand area detection algorithm form a background image by analyzing entropy in an image. With modified hand area detection algorithm, it was possible to recognize hand gestures from it. As a results, the experiments showed that the suggested algorithm was good at recognizing one's facial expression and hand gesture by detecting a dominant motion area on images without getting any limits from the background image.

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Hand Gesture Recognition using Optical Flow Field Segmentation and Boundary Complexity Comparison based on Hidden Markov Models

  • Park, Sang-Yun;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.14 no.4
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    • pp.504-516
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    • 2011
  • In this paper, we will present a method to detect human hand and recognize hand gesture. For detecting the hand region, we use the feature of human skin color and hand feature (with boundary complexity) to detect the hand region from the input image; and use algorithm of optical flow to track the hand movement. Hand gesture recognition is composed of two parts: 1. Posture recognition and 2. Motion recognition, for describing the hand posture feature, we employ the Fourier descriptor method because it's rotation invariant. And we employ PCA method to extract the feature among gesture frames sequences. The HMM method will finally be used to recognize these feature to make a final decision of a hand gesture. Through the experiment, we can see that our proposed method can achieve 99% recognition rate at environment with simple background and no face region together, and reduce to 89.5% at the environment with complex background and with face region. These results can illustrate that the proposed algorithm can be applied as a production.

Learning Algorithm for Multiple Distribution Data using Haar-like Feature and Decision Tree (다중 분포 학습 모델을 위한 Haar-like Feature와 Decision Tree를 이용한 학습 알고리즘)

  • Kwak, Ju-Hyun;Woen, Il-Young;Lee, Chang-Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.1
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    • pp.43-48
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    • 2013
  • Adaboost is widely used for Haar-like feature boosting algorithm in Face Detection. It shows very effective performance on single distribution model. But when detecting front and side face images at same time, Adaboost shows it's limitation on multiple distribution data because it uses linear combination of basic classifier. This paper suggest the HDCT, modified decision tree algorithm for Haar-like features. We still tested the performance of HDCT compared with Adaboost on multiple distributed image recognition.

Real-Time Earlobe Detection System on the Web

  • Kim, Jaeseung;Choi, Seyun;Lee, Seunghyun;Kwon, Soonchul
    • International journal of advanced smart convergence
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    • v.10 no.4
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    • pp.110-116
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    • 2021
  • This paper proposed a real-time earlobe detection system using deep learning on the web. Existing deep learning-based detection methods often find independent objects such as cars, mugs, cats, and people. We proposed a way to receive an image through the camera of the user device in a web environment and detect the earlobe on the server. First, we took a picture of the user's face with the user's device camera on the web so that the user's ears were visible. After that, we sent the photographed user's face to the server to find the earlobe. Based on the detected results, we printed an earring model on the user's earlobe on the web. We trained an existing YOLO v5 model using a dataset of about 200 that created a bounding box on the earlobe. We estimated the position of the earlobe through a trained deep learning model. Through this process, we proposed a real-time earlobe detection system on the web. The proposed method showed the performance of detecting earlobes in real-time and loading 3D models from the web in real-time.

A Real-time Interactive Shadow Avatar with Facial Emotions (감정 표현이 가능한 실시간 반응형 그림자 아바타)

  • Lim, Yang-Mi;Lee, Jae-Won;Hong, Euy-Seok
    • Journal of Korea Multimedia Society
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    • v.10 no.4
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    • pp.506-515
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    • 2007
  • In this paper, we propose a Real-time Interactive Shadow Avatar(RISA) which can express facial emotions changing as response of user's gestures. The avatar's shape is a virtual Shadow constructed from the real-time sampled picture of user's shape. Several predefined facial animations overlap on the face area of the virtual Shadow, according to the types of hand gestures. We use the background subtraction method to separate the virtual Shadow, and a simplified region-based tracking method is adopted for tracking hand positions and detecting hand gestures. In order to express smooth change of emotions, we use a refined morphing method which uses many more frames in contrast with traditional dynamic emoticons. RISA can be directly applied to the area of interface media arts and we expect the detecting scheme of RISA would be utilized as an alternative media interface for DMB and camera phones which need simple input devices, in the near future.

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