• Title/Summary/Keyword: Realtime Object Detection

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Implementation of a Task Level Pipelined Multicomputer RV860-PIPE for Computer Vision Applications (컴퓨터 비젼 응용을 위한 태스크 레벨 파이프라인 멀티컴퓨터 RV860-PIPE의 구현)

  • Lee, Choong-Hwan;Kim, Jun-Sung;Park, Kyu-Ho
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.1
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    • pp.38-48
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    • 1996
  • We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.

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Implementation of a Deep Learning based Realtime Fire Alarm System using a Data Augmentation (데이터 증강 학습 이용한 딥러닝 기반 실시간 화재경보 시스템 구현)

  • Kim, Chi-young;Lee, Hyeon-Su;Lee, Kwang-yeob
    • Journal of IKEEE
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    • v.26 no.3
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    • pp.468-474
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    • 2022
  • In this paper, we propose a method to implement a real-time fire alarm system using deep learning. The deep learning image dataset for fire alarms acquired 1,500 sheets through the Internet. If various images acquired in a daily environment are learned as they are, there is a disadvantage that the learning accuracy is not high. In this paper, we propose a fire image data expansion method to improve learning accuracy. The data augmentation method learned a total of 2,100 sheets by adding 600 pieces of learning data using brightness control, blurring, and flame photo synthesis. The expanded data using the flame image synthesis method had a great influence on the accuracy improvement. A real-time fire detection system is a system that detects fires by applying deep learning to image data and transmits notifications to users. An app was developed to detect fires by analyzing images in real time using a model custom-learned from the YOLO V4 TINY model suitable for the Edge AI system and to inform users of the results. Approximately 10% accuracy improvement can be obtained compared to conventional methods when using the proposed data.

Analysis of Rice Field Drought Area Using Unmanned Aerial Vehicle (UAV) and Geographic Information System (GIS) Methods (무인항공기와 GIS를 이용한 논 가뭄 발생지역 분석)

  • Park, Jin Ki;Park, Jong Hwa
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.3
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    • pp.21-28
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    • 2017
  • The main goal of this paper is to assess application of UAV (Unmanned Aerial Vehicle) remote sensing and GIS based images in detection and measuring of rice field drought area in South Korea. Drought is recurring feature of the climatic events, which often hit South Korea, bringing significant water shortages, local economic losses and adverse social consequences. This paper describes the assesment of the near-realtime drought damage monitoring and reporting system for the agricultural drought region. The system is being developed using drought-related vegetation characteristics, which are derived from UAV remote sensing data. The study area is $3.07km^2$ of Wonbuk-myeon, Taean-gun, Chungnam in South Korea. UAV images were acquired three times from July 4 to October 29, 2015. Three images of the same test site have been analysed by object-based image classification technique. Drought damaged paddy rices reached $754,362m^2$, which is 47.1 %. The NongHyeop Agricultural Damage Insurance accepted agricultural land of 4.6 % ($34,932m^2$). For paddy rices by UAV investigation, the drought monitoring and crop productivity was effective in improving drought assessment method.

Vision-based Motion Control for the Immersive Interaction with a Mobile Augmented Reality Object (모바일 증강현실 물체와 몰입형 상호작용을 위한 비전기반 동작제어)

  • Chun, Jun-Chul
    • Journal of Internet Computing and Services
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    • v.12 no.3
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    • pp.119-129
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    • 2011
  • Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. Especially, recent increasing demands for mobile augmented reality require the development of efficient interactive technologies between the augmented virtual object and users. This paper presents a novel approach to construct marker-less mobile augmented reality object and control the object. Replacing a traditional market, the human hand interface is used for marker-less mobile augmented reality system. In order to implement the marker-less mobile augmented system in the limited resources of mobile device compared with the desktop environments, we proposed a method to extract an optimal hand region which plays a role of the marker and augment object in a realtime fashion by using the camera attached on mobile device. The optimal hand region detection can be composed of detecting hand region with YCbCr skin color model and extracting the optimal rectangle region with Rotating Calipers Algorithm. The extracted optimal rectangle region takes a role of traditional marker. The proposed method resolved the problem of missing the track of fingertips when the hand is rotated or occluded in the hand marker system. From the experiment, we can prove that the proposed framework can effectively construct and control the augmented virtual object in the mobile environments.

A Hardware Design of Feature Detector for Realtime Processing of SIFT(Scale Invariant Feature Transform) Algorithm in Embedded Systems (임베디드 환경에서 SIFT 알고리즘의 실시간 처리를 위한 특징점 검출기의 하드웨어 구현)

  • Park, Chan-Il;Lee, Su-Hyun;Jeong, Yong-Jin
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.3
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    • pp.86-95
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    • 2009
  • SIFT is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vertices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3D image reconstructions and intelligent vision system for robots. In this paper, we implement a hardware to sift feature detection algorithm for real time processing in embedded systems. We estimate that the hardware implementation give a performance 25ms of $1,280{\times}960$ image and 5ms of $640{\times}480$ image at 100MHz. And the implemented hardware consumes 45,792 LUTs(85%) with Synplify 8.li synthesis tool.

A Implementation of Electronic Measurement Datum Point Monitoring S/W based on Object-Oriented Modeling for Multi Purpose and High Availability (다목적 및 고활용성을 위한 객체지향 모델링 기반의 전자 측량기준점 모니터링 S/W 구현)

  • Jung, Se-Hoon;Sim, Chun-Bo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.2
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    • pp.99-112
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    • 2015
  • Datum point for displaying location and altitude of point has being advantage usefully in various measurement parts. However, datum point has been increasing loss cases owing to weather changes and stratum changes and neglecting meaninglessly. In this paper, we design and implement a multi electronic measurement system monitoring software with functions such as include maximize utilization of existing measurement datum system as well as collected various environment data and detection stratum changes of surround area. Proposed software is implemented to support that reusability and extensibility of software using object oriented modeling method. Our software supports a GUI for electronic measurement datum point administrator as well as for web user and mobile user. Our system can support a graph GUI for various data analysis and reposition in realtime to database that measured location information and various sensing information to prevent loss of electronic measurement datum point and to detected stratum changes. In addition, we include a QR code and RFID recognition function. Finally, we suggest performance evaluation result to confirm stratum changes detection and GPS location error rate.

The Collision Processing Design of an Online Distributed Game Server (온라인 분산게임 서버의 충돌처리 설계)

  • Lee Sung-Ug
    • The Journal of the Korea Contents Association
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    • v.6 no.1
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    • pp.72-79
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    • 2006
  • Recently, a MMORPG(Massively Multi-play Online Role Playing Game) has built distribute server by Seamless world. This paper proposes an efficient collision detection method. DLS is used to dynamically adjust spatial subdivisions in each the boundary regions of distribute server We use an index table to effectively utilize the relationships between in the nodes and can perform the collision detection efficiently by reconstructing nodes of the tree. Also, we maintain the information for the boundary region to efficiently detect the collections and adjust the boundary regions between distributed servers by using DLS. As the DLS uses pointers, the information for each server is not needed and the boundary regions between the distributed servers are efficiently searched. Using node index points, the construction table can be made to find between ray and neighborhood node, In addition, processes for Network traffic reduce because a copy of the boundary regions is not needed when a object moves with realtime.

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