• Title/Summary/Keyword: pose estimation

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Detection of Smoking Behavior in Images Using Deep Learning Technology (딥러닝 기술을 이용한 영상에서 흡연행위 검출)

  • Dong Jun Kim;Yu Jin Choi;Kyung Min Park;Ji Hyun Park;Jae-Moon Lee;Kitae Hwang;In Hwan Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.4
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    • pp.107-113
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    • 2023
  • This paper proposes a method for detecting smoking behavior in images using artificial intelligence technology. Since smoking is not a static phenomenon but an action, the object detection technology was combined with the posture estimation technology that can detect the action. A smoker detection learning model was developed to detect smokers in images, and the characteristics of smoking behaviors were applied to posture estimation technology to detect smoking behaviors in images. YOLOv8 was used for object detection, and OpenPose was used for posture estimation. In addition, when smokers and non-smokers are included in the image, a method of separating only people was applied. The proposed method was implemented using Google Colab NVIDEA Tesla T4 GPU in Python, and it was found that the smoking behavior was perfectly detected in the given video as a result of the test.

NATURAL INTERACTION WITH VIRTUAL PET ON YOUR PALM

  • Choi, Jun-Yeong;Han, Jae-Hyek;Seo, Byung-Kuk;Park, Han-Hoon;Park, Jong-Il
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.341-345
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    • 2009
  • We present an augmented reality (AR) application for cell phone where users put a virtual pet on their palms and play/interact with the pet by moving their hands and fingers naturally. The application is fundamentally based on hand/palm pose recognition and finger motion estimation, which is the main concern in this paper. We propose a fast and efficient hand/palm pose recognition method which uses natural features (e.g. direction, width, contour shape of hand region) extracted from a hand image with prior knowledge for hand shape or geometry (e.g. its approximated shape when a palm is open, length ratio between palm width and pal height). We also propose a natural interaction method which recognizes natural motion of fingers such as opening/closing palm based on fingertip tracking. Based on the proposed methods, we developed and tested the AR application on an ultra-mobile PC (UMPC).

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Error Quantification of Photogrammetric 6DOF Pose Estimation (사진계측기반 6자유도 포즈 예측의 오차 정량화)

  • Kim, Sang-Jin;You, Heung-Cheol;Reu, Taekyu
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.5
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    • pp.350-356
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    • 2013
  • Photogrammetry has been widely used for measuring the important physical quantities in aerospace areas because it is a remote and non-contact measurement method. In this study, we analyzed photogrammetric error which can be occur in six degrees of freedom(6DOF) analysis among coordinates systems with single camera. Error analysis program were developed, and validated using geometric problem converted from imaging process. We analogized that the statistic from estimated camera pose which is need to 6DOF analysis is normally distributed, and quantified the photogrammetric error using estimated population standard deviation.

Laser pose calibration of ViSP for precise 6-DOF structural displacement monitoring

  • Shin, Jae-Uk;Jeon, Haemin;Choi, Suyoung;Kim, Youngjae;Myung, Hyun
    • Smart Structures and Systems
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    • v.18 no.4
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    • pp.801-818
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    • 2016
  • To estimate structural displacement, a visually servoed paired structured light system (ViSP) was proposed in previous studies. The ViSP is composed of two sides facing each other, each with one or two laser pointers, a 2-DOF manipulator, a camera, and a screen. By calculating the positions of the laser beams projected onto the screens and rotation angles of the manipulators, relative 6-DOF displacement between two sides can be estimated. Although the performance of the system has been verified through various simulations and experimental tests, it has a limitation that the accuracy of the displacement measurement depends on the alignment of the laser pointers. In deriving the kinematic equation of the ViSP, the laser pointers were assumed to be installed perfectly normal to the same side screen. In reality, however, this is very difficult to achieve due to installation errors. In other words, the pose of laser pointers should be calibrated carefully before measuring the displacement. To calibrate the initial pose of the laser pointers, a specially designed jig device is made and employed. Experimental tests have been performed to validate the performance of the proposed calibration method and the results show that the estimated displacement with the initial pose calibration increases the accuracy of the 6-DOF displacement estimation.

Fall Detection Algorithm Based on Machine Learning (머신러닝 기반 낙상 인식 알고리즘)

  • Jeong, Joon-Hyun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.226-228
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    • 2021
  • We propose a fall recognition system using the Pose Detection of Google ML kit using video data. Using the Pose detection algorithm, 33 three-dimensional feature points extracted from the body are used to recognize the fall. The algorithm that recognizes the fall by analyzing the extracted feature points uses k-NN. While passing through the normalization process in order not to be influenced in the size of the human body within the size of image and image, analyzing the relative movement of the feature points and the fall recognizes, thirteen of the thriteen test videos recognized the fall, showing an 100% success rate.

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Pose Estimation of Face Using 3D Model and Optical Flow in Real Time (3D 모델과 Optical flow를 이용한 실시간 얼굴 모션 추정)

  • Kwon, Oh-Ryun;Chun, Jun-Chul
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.780-785
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    • 2006
  • HCI, 비전 기반 사용자 인터페이스 또는 제스쳐 인식과 같은 많은 분야에서 3 차원 얼굴 모션을 추정하는 것은 중요한 작업이다. 연속된 2 차원 이미지로부터 3 차원 모션을 추정하기 위한 방법으로는 크게 외형 기반 방법이나 모델을 이용하는 방법이 있다. 본 연구에서는 동영상으로부터 3 차원 실린더 모델과 Optical flow를 이용하여 실시간으로 얼굴 모션을 추정하는 방법을 제안하고자 한다. 초기 프레임으로부터 얼굴의 피부색과 템플릿 매칭을 이용하여 얼굴 영역을 검출하고 검출된 얼굴 영역에 3 차원 실린더 모델을 투영하게 된다. 연속된 프레임으로 부터 Lucas-Kanade 의 Optical flow 를 이용하여 얼굴 모션을 추정한다. 정확한 얼굴 모션 추정을 하기 위해 IRLS 방법을 이용하여 각 픽셀에 대한 가중치를 설정하게 된다. 또한, 동적 템플릿을 이용해 오랫동안 정확한 얼굴 모션 추정하는 방법을 제안한다.

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Development of Intelligent Bed Robot System

  • Oh, Chang-Mok;Seo, Kap-Ho;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1535-1538
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    • 2004
  • In this paper, an Intelligent Bed Robot System (IBRS) is proposed, that is a special bed equipped with robot manipulator. To assist a patient using IBRS, pose and motion estimation process is fundamental. It is designed to help the elderly and the disabled for their independent life in bed without other assistants. For this purpose, we use the pressure sensor distributed mattress for detecting the change of motion on the bed. Using that data, we control the robot arm to move to the appropriate position and serve to the user. In addition, we can estimate the user's intention based on the change of pressure and use those data to control the robot arm guide.

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Evidence gathering for line based recognition by real plane

  • Lee, Jae-Kyu;Ryu, Moon-Wook;Lee, Jang-Won
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.195-199
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    • 2008
  • We present an approach to detect real plane for line base recognition and pose estimation Given 3D line segments, we set up reference plane for each line pair and measure the normal distance from the end point to the reference plane. And then, normal distances are measured between remains of line endpoints and reference plane to decide whether these lines are coplanar with respect to the reference plane. After we conduct this coplanarity test, we initiate visibility test using z-buffer value to prune out ambiguous planes from reference planes. We applied this algorithm to real images, and the results are found useful for evidence fusion and probabilistic verification to assist the line based recognition as well as 3D pose estimation.

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Robot Posture Estimation Using Inner-Pipe Image

  • Sup, Yoon-Ji;Sok, Kang-E
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.173.1-173
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    • 2001
  • This paper proposes the methodology in image processing algorithm that estimates the pose of the pipe crawling robot. The pipe crawling robots are usually equipped with a lighting device and a camera on its head for monitoring and inspection purpose. The proposed methodology is using these devices without introducing the extra sensors and is based on the fact that the position and the intensity of the reflected light varies with the robot posture. The algorithm is divided into two parts, estimating the translation and rotation angle of the camera, followed by the actual pose estimation of the robot. To investigate the performance of the algorithm, the algorithm is applied to a sewage maintenance robot.

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Pose Estimation of Mobile Robot Using Probabilistic Approach (확률론적 방법을 이용한 이동로봇 위치 추정 방법)

  • Ko, Nak-Yong;Seo, Dong-Jin;Kim, Tae-Gyun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2008.04a
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    • pp.43-45
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    • 2008
  • 위 인식은 이동 로봇의 자율 주행을 위한 필수 기능이다. 위치 추정을 위해서 Bayes Filter를 기본으로한 칼만 필터 방법들이 주로 제안되어졌고 최근에는 Particle Filter 방법이 제안되어져 사용되고 있다. 본 연구에서는 영역센서를 장착한 이동 로봇의 위치 추정을 위해 레이저 영역 센서를 이용하는 Particle Filter 방법을 구현하였다. Particle Filter방법은 Kalman Filter 방법에 비해서 구현이 간단하면서도 Kidnapping 문제에도 대응할 수 있는 장점이 있다. 본 연구를 통하여 위치 추정의 수렴도, 정확도, 그리고 Kidnapping 발생시의 위치 추정 성능등을 분석하여, 기존 방법의 성능을 개선하는 방법을 제안한다.

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