• 제목/요약/키워드: Object technology

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다중 이미지에서 단일 이미지 검출 및 추적 시스템 구현 (Implementation of a Single Image Detection and Tracking System in Multiple Images)

  • 최재학;박인호;김성윤;이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제16권3호
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    • pp.78-81
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    • 2017
  • Augmented Reality(AR) is the core technology of the future knowledge service industry. It is expected to be used in various fields such as medical, education, entertainment etc. Briefly, augmented reality technology is a technique in which a mapped virtual object is augmented when a real-world object is viewed through a device after mapping a real-world object and a virtual object. In this paper, we implemented object detection and tracking system, which is a key technology of augmented reality. To speed up the object tracking, the ORB algorithm, which is a lightweight algorithm compared to the detection algorithm, is applied. In addition, KNN classifier, which is a machine learning algorithm, was applied to detect a single object by learning multiple images.

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가상로봇과 실제로봇 사이의 운동 동기화를 통한 물체 인식 및 목표물 추적방안 (Object Recognition and Target Tracking Using Motion Synchronization between Virtual and Real Robots)

  • 안혜경;강현준;김진범;정지원;옥서원;김동환
    • 한국생산제조학회지
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    • 제26권1호
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    • pp.20-29
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    • 2017
  • Motion synchronization between developed real and virtual robots for object recognition and target tracking is introduced. ASUS's XTION PRO Live is implemented as a sensor and configured to recognize walls and obstacles, and perceive objects. In order to create virtual reality, Unity 3D is adopted to be associated with the real robot, and the virtual object is controlled by using an input device. A Bluetooth serial communication module is used for wireless communication between the PC and the real robot. The motion information of a virtual object controlled by the user is sent to the robot. Then, the robot moves in the same way as the virtual object according to the motion information. Through motion synchronization, two scenarios, which map the real space and current object information with virtual objects and space, were demonstrated, yielding good agreement between the two spaces.

A Salient Based Bag of Visual Word Model (SBBoVW): Improvements toward Difficult Object Recognition and Object Location in Image Retrieval

  • Mansourian, Leila;Abdullah, Muhamad Taufik;Abdullah, Lilli Nurliyana;Azman, Azreen;Mustaffa, Mas Rina
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권2호
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    • pp.769-786
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    • 2016
  • Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts.

사물인식을 위한 딥러닝 모델 선정 플랫폼 (Deep Learning Model Selection Platform for Object Detection)

  • 이한솔;김영관;홍지만
    • 스마트미디어저널
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    • 제8권2호
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    • pp.66-73
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    • 2019
  • 최근 컴퓨터 비전을 활용한 사물인식 기술이 센서 기반 사물인식 기술을 대체할 기술로 주목을 받고 있다. 센서 기반 사물인식 기술은 일반적으로 고가의 센서를 필요로 하기 때문에 기술이 상용화되기 어렵다는 문제가 있었다. 반면 컴퓨터 비전을 활용한 사물인식 기술은 고가의 센서 대신 비교적 저렴한 카메라를 사용할 수 있다. 동시에 CNN이 발전하면서 실시간 사물인식이 가능해진 이후 IoT, 자율주행자동차 등 타 분야에 활발하게 도입되고 있다. 그러나 사물 인식 모델을 상황에 알맞게 선택하고 학습시키기 위해서는 딥러닝에 대한 전문적인 지식을 요구하기 때문에 비전문가가 사물 인식 모델을 사용하기에는 어려움이 따른다. 따라서 본 논문에서는 딥러닝 기반 사물인식 모델들의 구조와 성능을 분석하고, 사용자가 원하는 조건의 최적의 딥러닝 기반 사물 인식 모델을 스스로 선정할 수 있는 플랫폼을 제안한다. 또한 통계에 기반한 사물 인식 모델 선정이 필요한 이유를 실험을 통해 증명한다.

Adaptive Thinning Algorithm for External Boundary Extraction

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • 제4권4호
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    • pp.75-80
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    • 2016
  • The process of extracting external boundary of an object is a very important process for recognizing an object in the image. The proposed extraction method consists of two processes: External Boundary Extraction and Thinning. In the first step, external boundary extraction process separates the region representing the object in the input image. Then, only the pixels adjacent to the background are selected among the pixels constituting the object to construct an outline of the object. The second step, thinning process, simplifies the outline of an object by eliminating unnecessary pixels by examining positions and interconnection relations between the pixels constituting the outline of the object obtained in the previous extraction process. As a result, the simplified external boundary of object results in a higher recognition rate in the next step, the object recognition process.

An Efficient Method of Scanning and Tracking for AR

  • Park, Yerang;Chin, Seongah
    • International Journal of Advanced Culture Technology
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    • 제7권4호
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    • pp.302-307
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    • 2019
  • In this paper, we propose an efficient method for AR toolkit Vuforia. In order to increase the scan rate when using the 3D object scanner, the scan rate parameters need to be analyzed in terms of the angle and distance. In addition, in order to increase the tracking rate when tracking an object, the tracking rate has to be evaluated according to the position, complexity, and contrast of the object. To this end, we have defined the difference of scan rate according to angle and distance between camera and object when using object scanner and the recognition time according to object's position, complexity and contrast when tracking object.

Object-based Multimedia Contents Storage for Mobile Devices

  • Nam, Young-Jin;Choi, Min-Seok;Nam, In-Gil
    • 한국정보기술응용학회:학술대회논문집
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    • 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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    • pp.31-34
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    • 2005
  • Mobile devices, such as PDAs, portable multimedia players, are more likely to encompass large storage devices with prevalance of high-quality multimedia contents. This paper proposes an object-based multimedia contents storage architecture that employs the object-based storage device model and the iSCSI protocol. It also provides a multimedia content player that operates directly with the proposed storage architecture. We implement both the proposed storage architecture and the multimedia content player upon the Linux environment. Performance evaluation by playing MP3 multimedia contents reveals that the proposed storage architecture reduces the total power consumption by 9%, compared with an existing networked storage. This enhancement is mainly contributed to the fact that a large portion of the file system is moved into the object-based multimedia contents storage from the mobile device.

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Augmented Reality Service Based on Object Pose Prediction Using PnP Algorithm

  • Kim, In-Seon;Jung, Tae-Won;Jung, Kye-Dong
    • International Journal of Advanced Culture Technology
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    • 제9권4호
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    • pp.295-301
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    • 2021
  • Digital media technology is gradually developing with the development of convergence quaternary industrial technology and mobile devices. The combination of deep learning and augmented reality can provide more convenient and lively services through the interaction of 3D virtual images with the real world. We combine deep learning-based pose prediction with augmented reality technology. We predict the eight vertices of the bounding box of the object in the image. Using the predicted eight vertices(x,y), eight vertices(x,y,z) of 3D mesh, and the intrinsic parameter of the smartphone camera, we compute the external parameters of the camera through the PnP algorithm. We calculate the distance to the object and the degree of rotation of the object using the external parameter and apply to AR content. Our method provides services in a web environment, making it highly accessible to users and easy to maintain the system. As we provide augmented reality services using consumers' smartphone cameras, we can apply them to various business fields.

A New Approach for Multiple Object Tracking ? Discrete Event based Multiple Object Tracking (DEMOT)

  • Kim, Chi-Ho;You, Bum-Jae;Kim, Hag-Bae;Oh, Sang-Rok
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1134-1139
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    • 2003
  • Tracking is a fundamental technique which is able to be applied to gesture recognition, visual surveillance, tangible agent and so forth. Especially, multiple object tracking has been extensively studied in recent years in order to perform many and more complicated tasks. In this paper, we propose a new approach of multiple object tracking which is based on discrete event. We call this system the DEMOT (Discrete Event based Multiple Object Tracking). This approach is based on the fact that a multiple object tracking can have just four situations - initiation, continuation, termination, and overlapping. Here, initiation, continuation, termination, and overlapping constitute a primary event set and this is based on the change of the number of extracted objects between a previous frame and a current frame. This system reduces computational costs and holds down the identity of all targets. We make experiments for this system with respect to the number of targets, each event, and processing period. We describe experimental results that show the successful multiple object tracking by using our approach.

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Implementation of an improved real-time object tracking algorithm using brightness feature information and color information of object

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • 한국컴퓨터정보학회논문지
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    • 제22권5호
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    • pp.21-28
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    • 2017
  • As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.