• 제목/요약/키워드: Multimedia Object

검색결과 896건 처리시간 0.022초

MPEG-4 플레이어에서 객체 우선 순위에 의한 장면 구성 (A Scene Composition by Object Priority Order on MPEG-4 Player)

  • 이윤주;이석필;조위덕;김상욱
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권3_4호
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    • pp.285-292
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    • 2003
  • 기존에 개발된 MPEG-4 플레이어들을 살펴보면, 객체의 삽입, 삭제, 갱신과 같은 사용자 상호작용에 의한 시청각 장면 프리젠테이션시 전체 미디어 객체를 다시 프리젠테이션해야 하므로 화면이 껌뻑이거나 프리젠테이션 속도가 느렸다. 본 논문에서는 이를 개선하기 위해 객체 우선 순위 컴포지션 방법을 제안한다. 이는 복합 미디어 객체로 구성된 시청각 장면을 사용자 상호자용에 의해 실시간으로 객체가 삽입, 삭제, 갱신되는 장면 변화를 보다 효율적으로 프리젠테이션하는 방법이다. 제안된 방법으로 구현한 결과는 MPEG-4 스트림의 즉각적이고 자연스러운 프리젠테이션이 가능함을 보여준다

Fast ROI Detection for Speed up in a CNN based Object Detection

  • Kim, Jin-Sung;Lee, Youhak;Lee, Kyujoong;Lee, Hyuk-Jae
    • Journal of Multimedia Information System
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    • 제6권4호
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    • pp.203-208
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    • 2019
  • Fast operation of a CNN based object detection is important in many application areas. It is an efficient approach to reduce the size of an input image. However, it is difficult to find an area that includes a target object with minimal computation. This paper proposes a ROI detection method that is fast and robust to noise. The proposed method is not affected by a flicker line noise that is a kind of aliasing between camera and LED light. Fast operation is achieved by using down-sampling efficiently. The accuracy of the proposed ROI detection method is 92.5% and the operation time for a frame with a resolution of 640 × 360 is 0.388msec.

컨볼루션 신경망의 특징맵을 사용한 객체 추적 (Object Tracking using Feature Map from Convolutional Neural Network)

  • 임수창;김도연
    • 한국멀티미디어학회논문지
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    • 제20권2호
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    • pp.126-133
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    • 2017
  • The conventional hand-crafted features used to track objects have limitations in object representation. Convolutional neural networks, which show good performance results in various areas of computer vision, are emerging as new ways to break through the limitations of feature extraction. CNN extracts the features of the image through layers of multiple layers, and learns the kernel used for feature extraction by itself. In this paper, we use the feature map extracted from the convolution layer of the convolution neural network to create an outline model of the object and use it for tracking. We propose a method to adaptively update the outline model to cope with various environment change factors affecting the tracking performance. The proposed algorithm evaluated the validity test based on the 11 environmental change attributes of the CVPR2013 tracking benchmark and showed excellent results in six attributes.

비디오를 위한 효율적인 프록시 서버 캐쉬의 관리 (Efficient Management of Proxy Server Cache for Video)

  • 조경산;홍병천
    • 한국시뮬레이션학회논문지
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    • 제12권2호
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    • pp.25-34
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    • 2003
  • Because of explosive growth in demand for web-based multimedia applications, proper proxy caching for large multimedia object (especially video) has become needed. For a video object which is much larger in size and has different access characteristics than the traditional web object such as image and text, caching the whole video file as a single web object is not efficient for the proxy cache. In this paper, we propose a proxy caching strategy with the constant-sized segment for video file and an improved proxy cache replacement policy. Through the event-driven simulation under various conditions, we show that our proposal is more efficient than the variable-sized segment strategy which has been proven to have higher hit ratio than other traditional proxy cache strategies.

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Web환경에서 멀티미디어 기반 문제은행 시스템의 구현 (Implementation of a Multimedia based ExamBank System in Web Environments)

  • 남인길;정소연
    • 한국산업정보학회논문지
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    • 제6권2호
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    • pp.54-62
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    • 2001
  • 본 논문에서는 웹 상에서 멀티미디어를 기반으로 한 문제은행 시스템을 제안하였다. 제안된 문제 은행 시스템은 객체-관계(Object-Relation)형 모델로 데이터베이스를 설계하고, 웹 환경에서 다수 클라이언트에 대한 무결성을 위해 독립적 실행이 되도록 Java 언어로 응용프로그램을 구현하였다. 문제 엔티티들은 객체로 정의하고, 이들간의 관계를 사용자 정의유형과 타입으로 설계 구현하였으며, DBMS의 스키마 객체와 JAVA Class를 매핑하여 DBMS와 어플리케이션 서버간에 체계화된 동작으로 객체를 전달할 수 있도록 하였다.

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Techniques for Background Updating under PTZ Camera Based Surveillance

  • Jung, Sung-Hoon;Kim, Min-Hwan
    • 한국멀티미디어학회논문지
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    • 제12권12호
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    • pp.1745-1754
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    • 2009
  • PTZ (Pan-Tilt-Zoom) camera based surveillance systems are enlarging their field of application due to their wide observable area. We aimed to detect both static and moving objects in automated working space by using a PTZ camera. For object detection we used background difference method because of the high quality segmentation. However, the method has a problem called 'hole' that is caused by non-continuous surveillance of the PTZ camera and its own characteristics. Moreover, the occlusion which occurs when the moving object overlaps with the static object should be solved for robust object detection. In this paper, we suggest a region-based technique for updating background images thereby overcoming the hole and occlusion problem. Through experiments with real scenes, it was verified that meaningful static and/or moving objects were detected very well.

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학습 객체 시퀀싱을 위한 컨텐츠 패키지 메타데이터 생성기 (Generator of Content Package Metadata for Learning Object Sequencing)

  • 국선화;박복자;정영식
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2003년도 추계학술발표대회(하)
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    • pp.897-900
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    • 2003
  • 본 논문에서는 SCORM 기반 시퀀싱 모델을 기반으로 학습객체의 구조에 대한 정보, 학습자에게 학습 객체를 어떻게 전달할 지를 결정하는 규칙 등을 포함하고 있는 컨텐츠 구조를 제시하고 학습 컨텐츠의 재사용과 공유가 가능하고 동일한 학습 컨텐츠에 서로 다른 교수법을 적용하여 교육의 효과를 달리할 수 있도록 시퀀싱을 위한 컨텐츠 패키지 메타데이터 생성기를 개발한다. 또한 학습자 정보 트래킹을 위한 SCO(Sharable Content Object)함수를 부착하여 학습 객체가 SCORM RTE(Run-Time Environment)와 통신 할 수 있도록 PIF(Package Interchange File)로 자동 패키징 시킨다.

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3차원 그래픽 산업을 위한 가구 인테리어 시스템 개발 (A Development of Furniture Interiol System for 3D Graphic Industry)

  • 윤용호;김종혁;김병수
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2004년도 춘계학술발표대회논문집
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    • pp.671-674
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    • 2004
  • 본 논문에서는 가구 인테리어를 위해 사전에 제작된 가구의 배치를 인터렉티브하게 시뮬레이션할 수 있도록 3D Visual 시뮬레이터 시스템을 개발하고자 한다. AutoCAD에서 제작된 도면파일(*.dxf)로 가상공간을 구성하고 3D MAX에서 Import된 Object 파일(*.3ds)을 Load하여 사용자가 쉽게 배치할 수 있도록 하는 것에 주안점을 두었다. 구성된 장면에 현실감을 주기 위해 고급 Rendering 기술 구현 또한 목표로 한다. 구축된 공간과 Object에는 텍스쳐 매핑과 Display Edit 기능을 구현하여 최대한 현실적인 시뮬레이터의 기능을 살릴 수 있도록 개발한다.

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An Approach to 3D Object Localization Based on Monocular Vision

  • Jung, Sung-Hoon;Jang, Do-Won;Kim, Min-Hwan
    • 한국멀티미디어학회논문지
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    • 제11권12호
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    • pp.1658-1667
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    • 2008
  • Reconstruction of 3D objects from a single view image is generally an ill-posed problem because of the projection distortion. A monocular vision based 3D object localization method is proposed in this paper, which approximates an object on the ground to a simple bounding solid and works automatically without any prior information about the object. A spherical or cylindrical object determined based on a circularity measure is approximated to a bounding cylinder, while the other general free-shaped objects to a bounding box or a bounding cylinder appropriately. For a general object, its silhouette on the ground is first computed by back-projecting its projected image in image plane onto the ground plane and then a base rectangle on the ground is determined by using the intuition that touched parts of the object on the ground should appear at lower part of the silhouette. The base rectangle is adjusted and extended until a derived bounding box from it can enclose the general object sufficiently. Height of the bounding box is also determined enough to enclose the general object. When the general object looks like a round-shaped object, a bounding cylinder that encloses the bounding box minimally is selected instead of the bounding box. A bounding solid can be utilized to localize a 3D object on the ground and to roughly estimate its volume. Usefulness of our approach is presented with experimental results on real image objects and limitations of our approach are discussed.

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다중 센서를 사용한 주행 환경에서의 객체 검출 및 분류 방법 (A New Object Region Detection and Classification Method using Multiple Sensors on the Driving Environment)

  • 김정언;강행봉
    • 한국멀티미디어학회논문지
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    • 제20권8호
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    • pp.1271-1281
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    • 2017
  • It is essential to collect and analyze target information around the vehicle for autonomous driving of the vehicle. Based on the analysis, environmental information such as location and direction should be analyzed in real time to control the vehicle. In particular, obstruction or cutting of objects in the image must be handled to provide accurate information about the vehicle environment and to facilitate safe operation. In this paper, we propose a method to simultaneously generate 2D and 3D bounding box proposals using LiDAR Edge generated by filtering LiDAR sensor information. We classify the classes of each proposal by connecting them with Region-based Fully-Covolutional Networks (R-FCN), which is an object classifier based on Deep Learning, which uses two-dimensional images as inputs. Each 3D box is rearranged by using the class label and the subcategory information of each class to finally complete the 3D bounding box corresponding to the object. Because 3D bounding boxes are created in 3D space, object information such as space coordinates and object size can be obtained at once, and 2D bounding boxes associated with 3D boxes do not have problems such as occlusion.