• Title/Summary/Keyword: Parts Image Recognition

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A Mobile Landmarks Guide : Outdoor Augmented Reality based on LOD and Contextual Device (모바일 랜드마크 가이드 : LOD와 문맥적 장치 기반의 실외 증강현실)

  • Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.1-21
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    • 2012
  • In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

A study on 3D Modeling Process & Rendering Image of CAD Program-With Case study on Cellular Phone Design- (캐드에 의한 3차원 모델링 제작과정과 렌더링 이미지 연출에 관한 연구-무선 이동 전화기 디자인 사례를 중심으로-)

  • 이대우
    • Archives of design research
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    • no.18
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    • pp.25-34
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    • 1996
  • Industrial design development methods and processes have changed in accordance with Industrial Information Age. These days, problems are created by existing methods and evaluation of design value , all problems concerned with time and finances sitaution have been made a subject of discussion. Development of design processes have been changed by the development of problem recognition and solving tools, and dpsign tpchnulugy havp hppn replaced by computer technology,Thus. software design processes linking thoughtware to hardware are used in the solution of design problems with many parts. In this study, 3D Modeling samples are presented, 3D Modeling can realise ' Ideas' to '3Dimentional Virtual Ohjects'. These effect and value are anle to decisively influence the process of design problem conference-ebealuation-solution.Proxesses of actual modeling and rendering are made as follows. By compusition of simple 20 drawings and shaping them into 30 objects, 30 solid models can be made. To prssent effectivley, we can make a sample model by varying camera views,light sourses,materials and colours etc. This sample is evaluated by various cumposition, methods and PERT(Program Evaluation and Review Technique). This cuncrete sample (tentative plan)is changed within the CAD SYSTEM by design evaluation, and then converted to flowchart of mass productive conception through refined data. So, that tentative plan can be conformed to design desire actuillly, to the utmost degree. Finally, this design process can be proposed as il new method in cuntrast with current methods. The aim of this study is to suggest effective evaluation methods of design outcome among many evaluating elements.

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Intelligent Motion Pattern Recognition Algorithm for Abnormal Behavior Detections in Unmanned Stores (무인 점포 사용자 이상행동을 탐지하기 위한 지능형 모션 패턴 인식 알고리즘)

  • Young-june Choi;Ji-young Na;Jun-ho Ahn
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.73-80
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    • 2023
  • The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.