• Title/Summary/Keyword: Moving Detection

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Automatic Generation of the Personal 3D Face Model (3차원 개인 얼굴 모델 자동 생성)

  • Ham, Sang-Jin;Kim, Hyoung-Gon
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.1
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    • pp.104-114
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    • 1999
  • This paper proposes an efficient method for the automatic generation of personalized 3D face model from color image sequence. To detect a robust facial region in a complex background, moving color detection technique based on he facial color distribution has been suggested. Color distribution and edge position information in the detected face region are used to extract the exact 31 facial feature points of the facial description parameter(FDP) proposed by MPEG-4 SNHC(Synthetic-Natural Hybrid Coding) adhoc group. Extracted feature points are then applied to the corresponding vertex points of the 3D generic face model composed of 1038 triangular mesh points. The personalized 3D face model can be generated automatically in less then 2 seconds on Pentium PC.

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Feature Extraction of Welds from Industrial Computed Radiography Using Image Analysis and Local Statistic Line-Clustering (산업용 CR 영상분석과 국부확률 선군집화에 의한 용접특징추출)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.103-110
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    • 2008
  • A reliable extraction of welded area is the precedent task before the detection of weld defects in industrial radiography. This paper describes an attempt to detect and extract the welded features of steel tubes from the computed radiography(CR) images. The statistical properties are first analyzed on over 160 sample radiographic images which represent either weld or non-weld area to identify the differences between them. The analysis is then proceeded by pattern classification to determine the clustering parameters. These parameters are the width, the functional match, and continuity. The observed weld image is processed line by line to calculate these parameters for each flexible moving window in line image pixel set. The local statistic line-clustering method is used as the classifier to recognize each window data as weld or non-weld cluster. The sequential procedure is to track the edge lines between two distinct regions by iterative calculation of threshold, and it results in extracting the weld feature. Our methodology is concluded to be effective after experiment with CR weld images.

DCT-based Digital Dropout Detection using SVM (SVM을 이용한 DCT 기반의 디지털 드롭아웃 검출)

  • Song, Gihun;Ryu, Byungyong;Kim, Jaemyun;Ahn, Kiok;Chae, Oksam
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.7
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    • pp.190-200
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    • 2014
  • The video-based system of the broadcasters and the video-related institutions have shifted from analogical to digital in worldwide. This migration process can generate a defect, digital dropout, in the quality of the contents. Moreover, there are limited researches focused on these kind of defects and those related have limitations. For that reason, we are proposing a new method for feature extraction emphasizing in the peculiar block pattern of digital dropout based on discrete cosine transform (DCT). For classification of error block, we utilize support vector machine (SVM) which can manage feature vectors efficiently. Further, the proposed method overcome the limitation of the previous one using continuity of frame by frame. It is using only the information of a single frame and works better even in the presence of fast moving objects, without the necessity of specific model or parameter estimation. Therefore, this approach is capable of detecting digital dropout only with minimal complexity.

NEW PHOTOMETRIC PIPELINE TO EXPLORE TEMPORAL AND SPATIAL VARIABILITY WITH KMTNET DEEP-SOUTH OBSERVATIONS

  • Chang, Seo-Won;Byun, Yong-Ik;Shin, Min-Su;Yi, Hahn;Kim, Myung-Jin;Moon, Hong-Kyu;Choi, Young-Jun;Cha, Sang-Mok;Lee, Yongseok
    • Journal of The Korean Astronomical Society
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    • v.51 no.5
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    • pp.129-142
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    • 2018
  • The DEEP-South (the Deep Ecliptic Patrol of the Southern Sky) photometric census of small Solar System bodies produces massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of multi-aperture photometry and FastBit indexing techniques for faster access to a portion of the DEEP-South year-one data. Our new pipeline is designed to perform automated point source detection, robust high-precision photometry and calibration of non-crowded fields which have overlap with previously surveyed areas. In this paper, we show some examples of catalog-based variability searches to find new variable stars and to recover targeted asteroids. We discover 21 new periodic variables with period ranging between 0.1 and 31 days, including four eclipsing binary systems (detached, over-contact, and ellipsoidal variables), one white dwarf/M dwarf pair candidate, and rotating variable stars. We also recover astrometry (< ${\pm}1-2$ arcsec level accuracy) and photometry of two targeted near-earth asteroids, 2006 DZ169 and 1996 SK, along with the small- (~0.12 mag) and relatively large-amplitude (~0.5 mag) variations of their dominant rotational signals in R-band.

Reliable Time Synchronization Protocol in Sensor Networks (센서 네트워크에서 신뢰성 있는 시각 동기 프로토콜)

  • Hwang So-Young;Jung Yeon-Su;Baek Yun-Ju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3A
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    • pp.274-281
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    • 2006
  • Sensor network applications need synchronized time extremely such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. This paper describes reliable time synchronization protocol (RTSP) for wireless sensor networks. In the proposed method, synchronization error is decreased by creating hierarchical tree with lower depth and reliability is improved by maintaining and updating information of candidate parent nodes. The RTSP reduces recovery time and communication overheads comparing to TPSN when there are topology changes owing to moving of nodes, running out of energy and physical crashes. Simulation results show that RTSP has about 20% better performance than TPSN in synchronization accuracy. And the number of message in the RTSP is $20%{\sim}60%$ lower than that in the TPSN when nodes are failed in the network. In case of different transmission range of nodes, the communication overhead in the RTSP is reduced up to 40% than that in the TPSN at the maximum.

Computer Vision-based Method of detecting a Approaching Vehicle or the Safety of a Bus Passenger Getting off (버스 승객의 안전한 하차를 위한 컴퓨터비전 기반의 차량 탐지 시스템 개발)

  • Lee Kwang-Soon;Lee Kyung-Bok;Rho Kwang-Hyun;Han Min-Hong
    • Journal of the Institute of Convergence Signal Processing
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    • v.6 no.1
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    • pp.1-7
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    • 2005
  • This paper describes the system for detecting vehicles in the rear and rear-side that access between sidewalk and bus stopped to city road at day by computer vision-based method. This system informs appearance of vehicles to bus driver and passenger for the safety of a bus passenger getting off. The camera mounted on the top portion of the bus exit door gets the rear and rear-side image of the bus whenever a bus stops at the stop. The system sets search area between bus and sidewalk from this image and detects a vehicle by using change of image and sobel filtering in this area. From a central point of the vehicle detected, we can find out the distance, speed and direction by its location, width and length. It alarms the driver and passengers when it's judged that dangerous situation for the passenger getting off happens. This experiment results in a detection rate more than 87% in driving by bus on the road.

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A CMOS Digital Image Sensor with a Feature-Driven Attention Module (특징기반 주의 모듈을 사용하는 CMOS 디지털 이미지 센서)

  • Park, Min-Chul;Cheoi, Kyung-Joo;Hamamoto, Takayuki
    • The KIPS Transactions:PartB
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    • v.15B no.3
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    • pp.189-196
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    • 2008
  • In this paper, a CMOS digital image sensor, which consists of A/D conversion, motion estimation circuits, and an attention module for ROI (Region of Interest) detection is presented. The functions of A/D conversion and motion estimation are implemented by $0.6{\mu}m$ CMOS processing circuit as hardware, and the attention module is implemented outside the circuit as software currently. Attention modules are taken to improve limited applications of the smart image sensor. The current smart image sensor responses to the changes of intensity, and uses the integration time to estimate motion. Therefore it is limited in its applications. To make up for inherent property of the sensor from circuit design and extend its applications we decide to introduce perception solutions to the image sensor. Attention modules for still and moving images are employed to achieve such purposes. The suggested approach makes the smart image sensor available with additional functions for such cases that motion estimation or intensity changes are not observed. Experimental result shows the usefulness and extension of the image sensor.

Video-based Intelligent Unmanned Fire Surveillance System (영상기반 지능형 무인 화재감시 시스템)

  • Jeon, Hyoung-Seok;Yeom, Dong-Hae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.516-521
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    • 2010
  • In this paper, we propose a video-based intelligent unmanned fire surveillance system using fuzzy color models. In general, to detect heat or smoke, a separate device is required for a fire surveillance system, this system, however, can be implemented by using widely used CCTV, which does not need separate devices and extra cost. The systems called video-based fire surveillance systems use mainly a method extracting smoke or flame from an input image only. The smoke is difficult to extract at night because of its gray-scale color, and the flame color depends on the temperature, the inflammable, the size of flame, etc, which makes it hard to extract the flame region from the input image. This paper deals with a intelligent fire surveillance system which is robust against the variation of the flame color, especially at night. The proposed system extracts the moving object from the input image, makes a decision whether the object is the flame or not by means of the color obtained by fuzzy color model and the shape obtained by histogram, and issues a fire alarm when the flame is spread. Finally, we verify the efficiency of the proposed system through the experiment of the controlled real fire.

Video Image Mosaicing Technique Using 3 Dimensional Multi Base Lines (3차원 다중 기선을 사용만 비데오 영상 모자이크 기술)

  • 전재춘;서용철
    • Korean Journal of Remote Sensing
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    • v.20 no.2
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    • pp.125-137
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    • 2004
  • In case of using image sequence taken from a moving camera along a road in an urban area, general video mosaicing technique based on a single baseline cannot create 2-D image mosaics. To solve the drawback, this paper proposed a new image mosaicing technique through 3-D multi-baselines that can create image mosaics in 3-D space. The core of the proposed method is that each image frame has a dependent baseline, an equation of first order, calculated by using ground control point (GCP) of optical flows. The proposed algorithm consists of 4 steps: calculation of optical flows using hierarchical strategy, calculation of camera exterior orientation, determination of multi-baselines, and seamless image mosaics. This paper realized and showed the proposed algorithm that can create efficient image mosaics in 3-D space from real image sequence.

Self-driving quarantine robot with chlorine dioxide system (이산화염소 시스템을 적용한 자율주행 방역 로봇)

  • Bang, Gul-Won
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.145-150
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    • 2021
  • In order to continuously perform quarantine in public places, it is not easy to secure manpower, but using self-driving-based robots can solve problems caused by manpower. Self-driving-based quarantine robots can continuously prevent the spread of harmful viruses and diseases in public institutions and hospitals without additional manpower. The location of the autonomous driving function was estimated by applying the Pinnacle filter algorithm, and the UV sterilization system and chlorine dioxide injection system were applied for quarantine. The driving time is more than 3 hours and the position error is 0.5m.Soon, the stop-avoidance function was operated at 95% and the obstacle detection distance was 1.5 m, and the automatic charge recovery was charged by moving to the charging cradle at the remaining 10% of the battery capacity. As a result of quarantine with an unmanned quarantine system, UV sterilization is 99% and chlorine dioxide is sterilized more than 95%, which can contribute to reducing enormous social costs.