• 제목/요약/키워드: Space object tracking

검색결과 140건 처리시간 0.026초

Appearance Based Object Identification for Mobile Robot Localization in Intelligent Space with Distributed Vision Sensors

  • Jin, TaeSeok;Morioka, Kazuyuki;Hashimoto, Hideki
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제4권2호
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    • pp.165-171
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    • 2004
  • Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

Human Tracking using Multiple-Camera-Based Global Color Model in Intelligent Space

  • Jin Tae-Seok;Hashimoto Hideki
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권1호
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    • pp.39-46
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    • 2006
  • We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

물체 추적을 위한 강화된 부분공간 표현 (Enhanced Representation for Object Tracking)

  • 윤석민;유한주;최진영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.408-410
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    • 2009
  • We present an efficient and robust measurement model for visual tracking. This approach builds on and extends work on subspace representations of measurement model. Subspace-based tracking algorithms have been introduced to visual tracking literature for a decade and show considerable tracking performance due to its robustness in matching. However the measures used in their measurement models are often restricted to few approaches. We propose a novel measure of object matching using Angle In Feature Space, which aims to improve the discriminability of matching in subspace. Therefore, our tracking algorithm can distinguish target from similar background clutters which often cause erroneous drift by conventional Distance From Feature Space measure. Experiments demonstrate the effectiveness of the proposed tracking algorithm under severe cluttered background.

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공간지능화를 위한 색상기반 파티클 필터를 이용한 다중물체추적 (Multiple Object Tracking with Color-Based Particle Filter for Intelligent Space)

  • 진태석;하시모토 히데키
    • 로봇학회논문지
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    • 제2권1호
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    • pp.21-28
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    • 2007
  • The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

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컬러 클러스터링 기법을 이용한 공간지능화의 다중이동물체 추척 기법 (A Study on Multi-Object Tracking Method using Color Clustering in ISpace)

  • 진태석;김현덕
    • 한국정보통신학회논문지
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    • 제11권11호
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    • pp.2179-2184
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    • 2007
  • 본 논문에서는 인간과 환경사이의 물리적 또는 심리적 인터액션을 통한 인간중심의 적절한 서비스를 제공하는 공간지능화(iSpace: Intelligent Space) 구현하고자 네트웍 센서 인식공간을 소개하고 있다. 영상 데이터 처리 및 정보 네트웍 기능을 갖는 다수의 컬러 CCD 카메라를 iSpace 공간에 분산 배치하였다. iSpace내의 정보획득을 위한 네트웍 센서를 분산 지능형 네트웍 디바이스(DIND: Distributed Intelligent Network Devices)라고 명명하고 있으며, 각 DIND는 일종의 클라이언트 역할을 수행하도록 하였으며, DIND는 카메라 센서를 이용하는 이른바 카메라 네트워크를 구성한 것으로 이를 통해 실내 환경을 인식하고 모델링 하며 공간 내 거주자의 의도를 인식하기 위한 시스템을 구축하였다.

Object Tracking in 3-D Space with Passive Acoustic Sensors using Particle Filter

  • Lee, Jin-Seok;Cho, Shung-Han;Hong, Sang-Jin;Lim, Jae-Chan;Oh, Seong-Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권9호
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    • pp.1632-1652
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    • 2011
  • This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

Video Image Tracking Technique Based On Shape-Based Matching Algorithm

  • Chen, Min-Hsin;Chen, Chi-Farn
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.882-884
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    • 2003
  • We present an application of digital video images for object tracking. In order to track a fixed object, which was shoot on a moving vehicle, this study develops a shape-based matching algorithm to implement the tracking task. Because the shape-based matching algorithm has scale and rotation invariant characteristics, therefore it can be used to calculate the similarity between two variant shapes. An experiment is performed to track the ship object in the open sea. The result shows that the proposed method can track the object in the video images even the shape change largely.

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Multi-Object Tracking using the Color-Based Particle Filter in ISpace with Distributed Sensor Network

  • Jin, Tae-Seok;Hashimoto, Hideki
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제5권1호
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    • pp.46-51
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    • 2005
  • Intelligent Space(ISpace) is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Simulations are carried out to evaluate the proposed performance. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.

인공지능 공간상의 다중객체 구분을 위한 컬러 패턴 인식과 추적 (Color Pattern Recognition and Tracking for Multi-Object Tracking in Artificial Intelligence Space)

  • 진태석
    • 한국산업융합학회 논문집
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    • 제27권2_2호
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    • pp.319-324
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    • 2024
  • In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

Mapping of Real-Time 3D object movement

  • Tengis, Tserendondog;Batmunkh, Amar
    • International Journal of Internet, Broadcasting and Communication
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    • 제7권2호
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    • pp.1-8
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    • 2015
  • Tracking of an object in 3D space performed in real-time is a significant task in different domains from autonomous robots to smart vehicles. In traditional methods, specific data acquisition equipments such as radars, lasers etc, are used. Contemporary computer technology development accelerates image processing, and it results in three-dimensional stereo vision to be used for localizing and object tracking in space. This paper describes a system for tracking three dimensional motion of an object using color information in real time. We create stereo images using pair of a simple web camera, raw data of an object positions are collected under realistic noisy conditions. The system has been tested using OpenCV and Matlab and the results of the experiments are presented here.