• Title/Summary/Keyword: Moving system

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Dense Optical flow based Moving Object Detection at Dynamic Scenes (동적 배경에서의 고밀도 광류 기반 이동 객체 검출)

  • Lim, Hyojin;Choi, Yeongyu;Nguyen Khac, Cuong;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.5
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    • pp.277-285
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    • 2016
  • Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

Moving Shadow Detection using Deep Learning and Markov Random Field (딥 러닝과 마르코프 랜덤필드를 이용한 동영상 내 그림자 검출)

  • Lee, Jong Taek;Kang, Hyunwoo;Lim, Kil-Taek
    • Journal of Korea Multimedia Society
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    • v.18 no.12
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    • pp.1432-1438
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    • 2015
  • We present a methodology to detect moving shadows in video sequences, which is considered as a challenging and critical problem in the most visual surveillance systems since 1980s. While most previous moving shadow detection methods used hand-crafted features such as chromaticity, physical properties, geometry, or combination thereof, our method can automatically learn features to classify whether image segments are shadow or foreground by using a deep learning architecture. Furthermore, applying Markov Random Field enables our system to refine our shadow detection results to improve its performance. Our algorithm is applied to five different challenging datasets of moving shadow detection, and its performance is comparable to that of state-of-the-art approaches.

The Correlation between Groundwater Level and Moving Average of Precipitation in Nakdong River Watershed (낙동강유역의 지하수위와 강우이동평균의 상관관계)

  • Yang, Jeong-Seok;Ahn, Tae-Yeon
    • The Journal of Engineering Geology
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    • v.17 no.4
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    • pp.507-510
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    • 2007
  • The correlation between groundwater level(GWL) and the moving average of precipitation was analyzed based on the observation data in Nakdong river watershed. The precipitation data was compared and analyzed with the GWL data from adjacent observation point to the precipitation gauge station. The correlation between the moving average of precipitation with several averaging periods and GWL were analyzed and we could choose the averaging period that produces maximum correlation. A severe drawdown was observed from December to April. The maximum correlations between GWL and the moving average of precipitation were occurred from 20-day to 80-day averaging period.

A Study on Parallel Processing System for Automatic Segmentation of Moving Object in Image Sequences

  • Lee, Hyung;Park, Jong-Won
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.429-432
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    • 2000
  • The new MPEG-4 video coding standard enables content-based functionalities. In order to support the philosophy of the MPEG-4 visual standard, each frame of video sequences should be represented in terms of video object planes (VOP’s). In other words, video objects to be encoded in still pictures or video sequences should be prepared before the encoding process starts. Therefore, it requires a prior decomposition of sequences into VOP’s so that each VOP represents a moving object. A parallel processing system is required an automatic segmentation to be processed in real-time, because an automatic segmentation is time consuming. This paper addresses the parallel processing: system for an automatic segmentation for separating moving object from the background in image sequences. The proposed parallel processing system comprises of processing elements (PE’s) and a multi-access memory system (MAMS). Multi-access memory system is a memory controller to perform parallel memory access with the variety of types: horizontal, vertical, and block access way. In order to realize these ways, a multi-access memory system consists of a memory module selection module, data routing modules, and an address calculation and routing module. The proposed system is simulated and evaluated by the CADENCE Verilog-XL hardware simulation package.

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Design and implementation of motion tracking based no double difference with PTZ control (PTZ 제어에 의한 이중차영상 기반의 움직임 추적 시스템의 설계 및 구현)

  • Yang Geum-Seok;Yang Seung Min
    • The KIPS Transactions:PartB
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    • v.12B no.3 s.99
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    • pp.301-312
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    • 2005
  • Three different cases should be considered for motion tracking: moving object with fixed camera, fixed object with moving camera and moving object with moving camera. Two methods are widely used for motion tracking: the optical flow method and the difference frame method. The optical new method is mainly used when either one, object or camera is fixed. This method tracks object using time-space vector which compares object position frame by frame. This method requires heavy computation, and is not suitable for real-time monitoring system such as DVR(Digital Video Recorder). The different frame method is used for moving object with fixed camera. This method tracks object by comparing the difference between background images. This method is good for real-time applications because computation is small. However, it is not applicable if the camera is moving. This thesis proposes and implements the motion tracking system using the difference frame method with PTZ(Pan-Tilt-Zoom) control. This system can be used for moving object with moving camera. Since the difference frame method is used, the system is suitable for real-time applications such as DVR.

A Development of a Collision Prevention System by a Moving Image (이동 영상에 의한 충돌 방지 시스템의 개발)

  • 박영식
    • Journal of the Institute of Convergence Signal Processing
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    • v.4 no.4
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    • pp.1-6
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    • 2003
  • In this Paper, the moving image is detected by a collision preventive system. The noise of these images is reduced by a mean filter. In case of detecting a movement with a binary difference image the moving area is detected exactly by the labeling and the projective method. When the image move slowly with the tracking mode of the system, the center of the tracking window move to the previous tracking window. And the tracking windows are divided into a tracking mode and a coasting mode which are determine by the Contrast-Difference Correlation of the date obtained from a difference image. The coasting mode determine whether continue the tracking step or not comparing the coasting-time values to reducing the error by the disturbance. The coasting and tracking of these moving images are verified by the result of the simulation.

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Development of Moving Objects Recognition and Tracking System on 360 Degree Panorama (360도 영상에서 이동 물체 감지 및 추적 시스템의 개발)

  • Ko, Kwang-Man;Joo, Su-Chong
    • Journal of Korea Multimedia Society
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    • v.21 no.2
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    • pp.289-299
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    • 2018
  • The 360 degree panoramas are picture of a wide range of images on one screen, so we can see a fairly wide range at a time. In particular, cylinderical panoramas are the most widely used spherical image, and its left and right viewing angles reach 360 degree, so you can observe front, rear, left, and right at once. Using 360 degree panorama, all directions can be monitored at the same time, so all directions can be effectively monitored compared to other methods. In this paper, we develop a system to recognize and track the movement of moving objects on a 360 degree panorama, and then present and verify the experimental results. For this goals, first, we developed a system to recognize moving objects in 360 degree panorama using DoF(Difference of Frame) algorithm. Second, based on the TLD algorithm, we developed an application that can track a specific single moving object in a 360 degree panorama and presented the experimental results.

Performance of a Novel Bioreactor Equipped with Moving Membrane Tube-Aeration System (회전하는 산소전달장치가 부착된 동물세포 배양기의 조업 성능에 관한 고찰)

  • Kim, Young-Nam;Jeon, Byung-Cheol;Lee, Jin-Ha;Lee, Hyeon-Yong
    • Microbiology and Biotechnology Letters
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    • v.21 no.4
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    • pp.348-353
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    • 1993
  • The optimal conditions for operating a moving-aeration bioreactor were determined as 30rpm and 150 (ml/min) of air flow rate, which can yield ca. 7.3 (l/h)of maximum mass transfer coefficient. It was also found that the agitation speed played much much important role than air input rate in oxgen transfer into the medium. $2.6{\times}10^6$ (cells/ml) and 0.6 (ml/l) of maximum cell denisty and IL-2 production were observed in batch cultivation of IL-2 producing BHK cell line. 0.53 (mM/l/h) of oxygen uptake rate was also estimated. The performance of a moving-aeration bioreactor (specific growth rate and oxygen uptake rate, etc.) was superior to other culture systems, such as cell-life and static membrane aeration bioreactors. Ii must be useful to apply this reactor to many culture processes by improving structural limitations in scaling-up the system.

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The Distributed Management System of Moving Objects for LBS

  • Jang, In-Sung;Cho, Dae-Soo;Park, Jong-Hyun
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.163-167
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    • 2002
  • Recently, owing to performance elevation of telecommunication technology, increase of wireless internet's subscriber and diffusion of wireless device, Interest about LBS (Location Based Service) which take advantage of user's location information and can receive information in concerning with user's location is increasing rapidly. So, MOMS (Moving Object Management System) that manage user's location information is required compulsorily to provide location base service. LBS of childhood such as service to find a friend need only current location, but to provide high-quality service in connection with Data Mining, CRM, We must be able to manage location information of past. In this paper, we design distributed manage system to insert and search Moving Object in a large amount. It has been consisted of CLIM (Current Location Information Manager), PLIM (Past-Location Information Manager) and BLIM (Distributed Location Information Manager). CLIM and PLIM prove performance of searching data by using spatiotemporal-index. DLIM distribute an enormous amount of location data to various database. Thus it keeps load-balance, regulates overload and manage a huge number of location information efficiently.

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Real Time System Realization for Binocular Eyeball Tracking Mouse (실시간 쌍안구 추적 마우스 시스템 구현에 관한 연구)

  • Ryu Kwang-Ryol;Choi Duck-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.9
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    • pp.1671-1678
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    • 2006
  • A real time system realization for binocular eyeball tracking mouse on the computer monitor being far from 30-40cm is presented in the paper. The processing for searching eyeball and tracking the cursor are that a facial image is acquired by the small CCD camera, convert it into binary image, search for the eye two using the five region mask method in the eye surroundings and the side four points diagonal positioning method is searched the each iris. The tracking cursor is matched by measuring the iris central moving position. The cursor controlling is achieved by comparing two related distances between the iris maximum moving and the cursor moving to calculate the moving distance from gazing position and screen. The experimental results show that the binocular eyeball mouse system is simple and fast to be real time.