• Title/Summary/Keyword: motion of object

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Flexible object manipulation using dual manipulators

  • Kosuge, Kazuhiro;Hashimoto, Satoshi
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.251-254
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    • 1996
  • We propose a coordinated motion control algorithm of dual manipulators handling a flexible object. The controller is designed so that it can specify the apparent impedance of the object as well as can control its deformation. The experimental results will illustrate validity of the proposed algorithm.

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Feature based Object Tracking from an Active Camera (능동카메라 환경에서의 특징기반의 이동물체 추적)

  • 오종안;정영기
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.141-144
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    • 2002
  • This paper describes a new feature based tracking system that can track moving objects with a pan-tilt camera. We extract corner features of the scene and tracks the features using filtering, The global motion energy caused by camera movement is eliminated by finding the maximal matching position between consecutive frames using Pyramidal template matching. The region of moving object is segmented by clustering the motion trajectories and command the pan-tilt controller to follow the object such that the object will always lie at the center of the camera. The proposed system has demonstrated good performance for several video sequences.

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3D Object's shape and motion recovery using stereo image and Paraperspective Camera Model (스테레오 영상과 준원근 카메라 모델을 이용한 객체의 3차원 형태 및 움직임 복원)

  • Kim, Sang-Hoon
    • The KIPS Transactions:PartB
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    • v.10B no.2
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    • pp.135-142
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    • 2003
  • Robust extraction of 3D object's features, shape and global motion information from 2D image sequence is described. The object's 21 feature points on the pyramid type synthetic object are extracted automatically using color transform technique. The extracted features are used to recover the 3D shape and global motion of the object using stereo paraperspective camera model and sequential SVD(Singuiar Value Decomposition) factorization method. An inherent error of depth recovery due to the paraperspective camera model was removed by using the stereo image analysis. A 30 synthetic object with 21 features reflecting various position was designed and tested to show the performance of proposed algorithm by comparing the recovered shape and motion data with the measured values.

Implementation of A 3-D Animation System Based on The MPEG-4 SNHC Standard (MPEG-4 SNHC 표준을 따르는 3차원 애니메이션 시스템의 구현)

  • 윤승욱;안정환;전정희;호요성
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.129-132
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    • 2002
  • In this paper, we propose a 3-D animation system to track and analyze motion of the human object. The proposed system consists of two separate layers: motion analysis layer and 3-D model registration layer. Following the MPEG-4 SNHC standard, we generate object motion using body definition and animation parameters. In the implemented system, we acquire human motion data from a single camera and extract body definition parameters from arbitrary VRML human models.

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Moving object segmentation using Markov Random Field (마코프 랜덤 필드를 이용한 움직이는 객체의 분할에 관한 연구)

  • 정철곤;김중규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.3A
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    • pp.221-230
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    • 2002
  • This paper presents a new moving object segmentation algorithm using markov random field. The algorithm is based on signal detection theory. That is to say, motion of moving object is decided by binary decision rule, and false decision is corrected by markov random field model. The procedure toward complete segmentation consists of two steps: motion detection and object segmentation. First, motion detection decides the presence of motion on velocity vector by binary decision rule. And velocity vector is generated by optical flow. Second, object segmentation cancels noise by Bayes rule. Experimental results demonstrate the efficiency of the presented method.

A Joint Motion Planning Based on a Bio-Mimetic Approach for Human-like Finger Motion

  • Kim Byoung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.217-226
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    • 2006
  • Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

Adaptive Color Snake Model for Real-Time Object Tracking

  • Seo, Kap-Ho;Jang, Byung-Gi;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.740-745
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    • 2003
  • Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.

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Dense Optical flow based Moving Object Detection at Dynamic Scenes (동적 배경에서의 고밀도 광류 기반 이동 객체 검출)

  • Lim, Hyojin;Choi, Yeongyu;Nguyen Khac, Cuong;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.11 no.5
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    • pp.277-285
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    • 2016
  • Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.

A Moving Object Tracking System from a Moving Camera by Integration of Motion Estimation and Double Difference (BBME와 DD를 통합한 움직이는 카메라로부터의 이동물체 추적 시스템)

  • 설성욱;송진기;장지혜;이철헌;남기곤
    • Journal of KIISE:Software and Applications
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    • v.31 no.2
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    • pp.173-181
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    • 2004
  • In this paper, we propose a system for automatic moving object detection and tracking in sequence images acquired from a moving camera. The proposed algorithm consists of moving object detection and its tracking. Moving object can be detected by integration of BBME and DD method We segment the detected object using histogram back projection, match it using histogram intersection, extract and track it using XY-projection. Computer simulation results have shown that the proposed algorithm is reliable and can successfully detect and track a moving object on image sequences obtained by a moving camera.

Real-time Projectile Motion Trajectory Estimation Considering Air Resistance of Obliquely Thrown Object Using Recursive Least Squares Estimation (비스듬히 던진 물체의 공기저항을 고려한 재귀 최소 자승법 기반 실시간 포물선 운동 궤적 추정)

  • Jeong, Sangyoon;Chwa, Dongkyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.3
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    • pp.427-432
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    • 2018
  • This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.