• Title/Summary/Keyword: Body Parts Detection

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A Study on multi-channel temperature monitoring for the detection of leakage or seepage in dam body (댐 침투수 탐지를 위한 멀티 채널 온도 모니터링 연구)

  • Oh, Seok-Hoon;Kim, Jung-Yul;Park, Han-Gyu;Kim, Hyoung-Soo;Kim, Yoo-Sung
    • Proceedings of the Korean Geotechical Society Conference
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    • 2005.03a
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    • pp.1211-1218
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    • 2005
  • Temperature variation according to space and time on the inner parts of engineering constructions(e.g.: dam, slope) can be a basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation(e.g.: cracks, defects) could be occurred by various factors. Seepage or leakage of water through these cracks or defects in old dams will directly cause temperature anomaly. Groundwater level also can be easily observed by abrupt change of temperature on the level. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For this, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body.

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A study on measurement and compensation of automobile door gap using optical triangulation algorithm (광 삼각법 측정 알고리즘을 이용한 자동차 도어 간격 측정 및 보정에 관한 연구)

  • Kang, Dong-Sung;Lee, Jeong-woo;Ko, Kang-Ho;Kim, Tae-Min;Park, Kyu-Bag;Park, Jung Rae;Kim, Ji-Hun;Choi, Doo-Sun;Lim, Dong-Wook
    • Design & Manufacturing
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    • v.14 no.1
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    • pp.8-14
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    • 2020
  • In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

Analysis of temperature monitoring data for leakage detection of earth dam (흙댐의 누수구역 판별을 위한 온도 모니터링 자료의 해석)

  • Oh, Seok-Hoon;Seo, Baek-Soo
    • Journal of Industrial Technology
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    • v.28 no.B
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    • pp.39-45
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    • 2008
  • Temperature variation according to space and time on the inner parts of engineering constructions(e.g.: dam, slope) can be a basic information for diagnosing their safety problem. In general, as constructions become superannuated, structural deformation(e.g.: cracks, defects) could be occurred by various factors. Seepage or leakage of water through these cracks or defects in old dams will directly cause temperature anomaly. Groundwater level also can be easily observed by abrupt change of temperature on the level. This study shows that the position of seepage or leakage in dam body can be detected by multi-channel temperature monitoring using thermal line sensor. For this, diverse temperature monitoring experiments for a leakage physical model were performed in the laboratory. In field application of an old earth fill dam, temperature variations for water depth and for inner parts of boreholes located at downstream slope were measured. Temperature monitoring results for a long time at the bottom of downstream slope of the dam showed the possibility that temperature monitoring can provide the synthetic information about flowing path and quantity of seepage of leakage in dam body.

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2D Human Pose Estimation based on Object Detection using RGB-D information

  • Park, Seohee;Ji, Myunggeun;Chun, Junchul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.800-816
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    • 2018
  • In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

A Method for Body Keypoint Localization based on Object Detection using the RGB-D information (RGB-D 정보를 이용한 객체 탐지 기반의 신체 키포인트 검출 방법)

  • Park, Seohee;Chun, Junchul
    • Journal of Internet Computing and Services
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    • v.18 no.6
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    • pp.85-92
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    • 2017
  • Recently, in the field of video surveillance, a Deep Learning based learning method has been applied to a method of detecting a moving person in a video and analyzing the behavior of a detected person. The human activity recognition, which is one of the fields this intelligent image analysis technology, detects the object and goes through the process of detecting the body keypoint to recognize the behavior of the detected object. In this paper, we propose a method for Body Keypoint Localization based on Object Detection using RGB-D information. First, the moving object is segmented and detected from the background using color information and depth information generated by the two cameras. The input image generated by rescaling the detected object region using RGB-D information is applied to Convolutional Pose Machines for one person's pose estimation. CPM are used to generate Belief Maps for 14 body parts per person and to detect body keypoints based on Belief Maps. This method provides an accurate region for objects to detect keypoints an can be extended from single Body Keypoint Localization to multiple Body Keypoint Localization through the integration of individual Body Keypoint Localization. In the future, it is possible to generate a model for human pose estimation using the detected keypoints and contribute to the field of human activity recognition.

Drowsiness Sensing System by Detecting Eye-blink on Android based Smartphones

  • Vununu, Caleb;Seung, Teak-Young;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.797-807
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    • 2016
  • The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

Automatic Intelligent Asymmetry Detection Using Digital Infrared Imaging with K-Means Clustering

  • Kim, Kwang Baek;Song, Doo Hoen
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.3
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    • pp.180-185
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    • 2015
  • Digital infrared thermal imaging is a non-invasive adjunctive diagnostic technique that allows an examiner to visualize and quantify changes in skin surface temperature. The asymmetry of temperature differences between the diseased and the contralateral healthy body parts can be automatically analyzed and has been studied in many areas of medical science. In this paper, we propose a method for intelligent automatic asymmetry detection based on a K-means analysis and a YCbCr color model. The implemented software successfully visualizes an asymmetric distribution of colors with respect to the patients’ health status.

Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map

  • Farooq, Adnan;Jalal, Ahmad;Kamal, Shaharyar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.5
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    • pp.1856-1869
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    • 2015
  • This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

Real Time Drowsiness Detection by a WSN based Wearable ECG Measurement System

  • Takalokastari, Tiina;Jung, Sang-Joong;Lee, Duk-Dong;Chung, Wan-Young
    • Journal of Sensor Science and Technology
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    • v.20 no.6
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    • pp.382-387
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    • 2011
  • Whether a person is feeling sleepy or reasonably awake is important safety information in many areas, such as humans operating in traffic or in heavy industry. The changes of body signals have been mostly researched by looking at electroencephalogram(EEG) signals but more and more other medical signals are being examined. In our study, an electrocardiogram(ECG) signal is measured at a sampling rate of 100 Hz and used to try to distinguish the possible differences in signal between the two states: awake and drowsy. Practical tests are conducted using a wireless sensor node connected to a wearable ECG sensor, and an ECG signal is transmitted wirelessly to a base station connected to a server PC. Through the QRS complex in the ECG analysis it is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. A program is made with MATLAB for digital signal filtering and graphing as well as recognizing the parts of the QRS complex within the signal. Drowsiness detection is performed by evaluating the R peaks, R-R interval, interval between R and S peaks and the duration of the QRS complex..

Detection of Radial Pulse by Combinational Fiber-optic Transducer (조합형 광섬유 트랜스듀서에 의한 요골맥파의 검출)

  • Park, Seung-Hwan;Hong, Seung-Hong
    • Journal of Sensor Science and Technology
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    • v.7 no.3
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    • pp.197-202
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    • 1998
  • The human pulse wave is a vital biosignal that includes the diagnostic data related with the heart and the cardiovascular system of human body. Based on the mechanical transducing method, a pulse detection transducer using optical fiber was developed to acquire the pulses non-invasively. To improve the detection efficiency, we proposed a new design that consists of two combinational parts; detecting part, which is in contact with the pulsating skin and transmits the displacement motion of the pulsating skin to the sensing part, and sensing part, which converts the physical quantity transmitted from the detecting part to electronic signal. By using the new method, we confirmed that the proposed transducer can detect the C point(incisura) and the T wave(tidal wave) which is not easily detected by existing transducers.

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