• Title/Summary/Keyword: object-based approach

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Multi-robot Mapping Using Omnidirectional-Vision SLAM Based on Fisheye Images

  • Choi, Yun-Won;Kwon, Kee-Koo;Lee, Soo-In;Choi, Jeong-Won;Lee, Suk-Gyu
    • ETRI Journal
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    • v.36 no.6
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    • pp.913-923
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    • 2014
  • This paper proposes a global mapping algorithm for multiple robots from an omnidirectional-vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas-Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi-robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional-vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.

Database Design for an Urban Geographic Information System based on an Object-oriented Approach (객체지향접근방식을 기반으로 한 도시지리정보시스템의 데이터베이스 설계에 관한 연구)

  • Ock, Han-Suk;Kim, Gap-Youl;Kim, Chang-Hwan;Kim, Sang-Wook
    • Journal of the Korean Association of Geographic Information Studies
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    • v.1 no.2
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    • pp.56-66
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    • 1998
  • The primary goal of the database design is to organize a large amount of data effectively in users and systems view point. Effective design of a database is very important for processing applications efficiently. In this paper, we discuss database design for an urban geographic information system that effectively maintains the cadastral and planimetric information. We first collect and analyze the requirements for the target urban geographic information system and then perform database design for these requirements. Our database design is based on the object-oriented approach that has rich expressive power and good reusability in comparison with the traditional relational approach. Especially, we employ the OMT, one of the most widely-used object-oriented models. We expect that our result would be helpful in building large databases for urban geographic information systems practically.

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Intelligent Query Processing in Deductive and Object-Oriented Databases (추론적 기법을 사용한 객체지향 데이터베이스의 지능적인 질의 처리)

  • Kim, Yang-Hee
    • Journal of Intelligence and Information Systems
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    • v.9 no.1
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    • pp.251-267
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    • 2003
  • In order to satisfy the needs of an intelligent information system, it is necessary to have more intelligent query processing in an object-oriented database. In this paper, we present a method to apply intelligent query processing in object-oriented databases using deductive approach. Using this method, we generate intelligent answers to represent the answer-set abstractly for a given query in object-oriented databases. Our approach consists of few stages: rule representation, rule reformation pre-resolution, and resolution. In rule representation, a set of deductive rules is generated based on an object-oriented database schema. In rule reformation, we eliminate the recursion in rules. In pre-resolution, rule transformation is done to get unique intensional literals. In resolution, we use SLD-resolution to generate intensional answers.

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Hierarchical Active Shape Model-based Motion Estimation for Real-time Tracking of Non-rigid Object (계층적 능동형태 모델을 이용한 비정형 객체의 움직임 예측형 실시간 추적)

  • 강진영;이성원;신정호;백준기
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.1-11
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    • 2004
  • In this paper we proposed a hierarchical ASM for real-time tracking of non-rigid objects. For tracking an object we used ASM for estimating object contour possibly with occlusion. Moreover, to reduce the processing time we used hierarchical approach for real-time tacking. In the next frame we estimated the initial feature point by using Kalman filter. We also added block matching algorithm for increasing accuracy of the estimation. The proposed hierarchical, prediction-based approach was proven to out perform the exiting non-hierarchical, non-prediction methods.

Object Categorization Using PLSA Based on Weighting (특이점 가중치 기반 PLSA를 이용한 객체 범주화)

  • Song, Hyun-Chul;Whoang, In-Teck;Choi, Kwang-Nam
    • Journal of Internet Computing and Services
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    • v.10 no.4
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    • pp.45-54
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    • 2009
  • In this paper we propose a new approach that recognizes the similar categories by weighting distinctive features. The approach is based on the PLSA that is one of the effective methods for the object categorization. PLSA is introduced from the information retrieval of text domain. PLSA, unsupervised method, shows impressive performance of category recognition. However, it shows relatively low performance for the similar categories which have the analog distribution of the features. In this paper, we consider the effective object categorization for the similar categories by weighting the mainly distinctive features. We present that the proposed algorithm, weighted PLSA, recognizes similar categories. Our method shows better results than the standard PLSA.

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Development of Personal Mobility Safety Assistants using Object Detection based on Deep Learning (딥러닝 기반 객체 인식을 활용한 퍼스널 모빌리티 안전 보조 시스템 개발)

  • Kwak, Hyeon-Seo;Kim, Min-Young;Jeon, Ji-Yong;Jeong, Eun-Hye;Kim, Ju-Yeop;Hyeon, So-Dam;Jeong, Jin-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.3
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    • pp.486-489
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    • 2021
  • Recently, the demand for the use of personal mobility vehicles, such as an electric kickboard, is increasing explosively because of its high portability and usability. However, the number of traffic accidents caused by personal mobility vehicles has also increased rapidly in recent years. To address the issues regarding the driver's safety, we propose a novel approach that can monitor context information around personal mobility vehicles using deep learning-based object detection and smartphone captured videos. In the proposed framework, a smartphone is attached to a personal mobility device and a front or rear view is recorded to detect an approaching object that may affect the driver's safety. Through the detection results using YOLOv5 model, we report the preliminary results and validated the feasibility of the proposed approach.

Kinematic Method of Camera System for Tracking of a Moving Object

  • Jin, Tae-Seok
    • Journal of information and communication convergence engineering
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    • v.8 no.2
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    • pp.145-149
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    • 2010
  • In this paper, we propose a kinematic approach to estimating the real-time moving object. A new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time path to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.

Controlling robot by image-based visual servoing with stereo cameras

  • Fan, Jun-Min;Won, Sang-Chul
    • Proceedings of the Korea Society of Information Technology Applications Conference
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    • 2005.11a
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    • pp.229-232
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    • 2005
  • In this paper, an image-based "approach-align -grasp" visual servo control design is proposed for the problem of object grasping, which is based on the binocular stand-alone system. The basic idea consists of considering a vision system as a specific sensor dedicated a task and included in a control servo loop, and we perform automatic grasping follows the classical approach of splitting the task into preparation and execution stages. During the execution stage, once the image-based control modeling is established, the control task can be performed automatically. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories by using the Jacobian matrix, which is proved by the Lyapunov stability theory. And we also stress the importance of projective invariant object/gripper alignment. The alignment between two solids in 3-D projective space can be represented with view-invariant, more precisely; it can be easily mapped into an image set-point without any knowledge about the camera parameters. The main feature of this method is that the accuracy associated with the task to be performed is not affected by discrepancies between the Euclidean setups at preparation and at task execution stages. Then according to the projective alignment, the set point can be computed. The robot gripper will move to the desired position with the image-based control law. In this paper we adopt a constant Jacobian online. Such method describe herein integrate vision system, robotics and automatic control to achieve its goal, it overcomes disadvantages of discrepancies between the different Euclidean setups and proposes control law in binocular-stand vision case. The experimental simulation shows that such image-based approach is effective in performing the precise alignment between the robot end-effector and the object.

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3D Object Recognition for Localization of Outdoor Robotic Vehicles (실외 주행 로봇의 위치 추정을 위한 3 차원 물체 인식)

  • Baek, Seung-Min;Kim, Jae-Woong;Lee, Jang-Won;Zhaojin, Lu;Lee, Suk-Han
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.200-204
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    • 2008
  • In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.

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Object Tracking for a Video Sequence from a Moving Vehicle: A Multi-modal Approach

  • Hwang, Tae-Hyun;Cho, Seong-Ick;Park, Jong-Hyun;Choi, Kyoung-Ho
    • ETRI Journal
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    • v.28 no.3
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    • pp.367-370
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    • 2006
  • This letter presents a multi-modal approach to tracking geographic objects such as buildings and road signs in a video sequence recorded from a moving vehicle. In the proposed approach, photogrammetric techniques are successfully combined with conventional tracking methods. More specifically, photogrammetry combined with positioning technologies is used to obtain 3-D coordinates of chosen geographic objects, providing a search area for conventional feature trackers. In addition, we present an adaptive window decision scheme based on the distance between chosen objects and a moving vehicle. Experimental results are provided to show the robustness of the proposed approach.

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