• Title/Summary/Keyword: real time motion tracking

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Real-Time Object Tracking and Segmentation Using Adaptive Color Snake Model

  • Seo Kap-Ho;Shin Jin-Ho;Kim Won;Lee Ju-Jang
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.236-246
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    • 2006
  • Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks such as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. In this paper, the development of new snake model called 'adaptive color snake model (ACSM)' for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. For robust tracking, the condensation algorithm was adopted to control the parameters of ACSM. The effectiveness of the ACSM is verified by appropriate simulations and experiments.

Real-Time Tracking of Human Location and Motion using Cameras in a Ubiquitous Smart Home

  • Shin, Dong-Kyoo;Shin, Dong-Il;Nguyen, Quoc Cuong;Park, Se-Young
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.3 no.1
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    • pp.84-95
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    • 2009
  • The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

Localized evaluation of actuator tracking for real-time hybrid simulation using frequency-domain indices

  • Xu, Weijie;Guo, Tong;Chen, Cheng
    • Structural Engineering and Mechanics
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    • v.62 no.5
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    • pp.631-642
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    • 2017
  • Accurate actuator tracking plays an important role in real-time hybrid simulation (RTHS) to ensure accurate and reliable experimental results. Frequency-domain evaluation index (FEI) interprets actuator tracking into amplitude and phase errors thus providing a promising tool for quantitative assessment of real-time hybrid simulation results. Previous applications of FEI successfully evaluated actuator tracking over the entire duration of the tests. In this study, FEI with moving window technique is explored to provide post-experiment localized actuator tracking assessment. Both moving window with and without overlap are investigated through computational simulations. The challenge is discussed for Fourier Transform to satisfy both time domain and frequency resolution for selected length of moving window. The required data window length for accuracy is shown to depend on the natural frequency and structural nonlinearity as well as the ground motion input for both moving windows with and without overlap. Moving window without overlap shows better computational efficiency and has potential for future online evaluation. Moving window with overlap however requires much more computational efforts and is more suitable for post-experiment evaluation. Existing RTHS data from Network Earthquake Engineering Simulation (NEES) is utilized to further demonstrate the effectiveness of the proposed approaches. It is demonstrated that with proper window size, FEI with moving window techniques enable accurate localized evaluation of actuator tracking for real-time hybrid simulation.

Real-time Water Quality Monitoring System Using Vision Camera and Multiple Objects Tracking Method (비젼 카메라와 다중 객체 추적 방법을 이용한 실시간 수질 감시 시스템)

  • Yang, Won-Keun;Lee, Jung-Ho;Cho, Ik-Hwan;Jin, Ju-Kyong;Jeong, Dong-Seok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.4C
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    • pp.401-410
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    • 2007
  • In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

A LOCALIZED GLOBAL DEFORMATION MODEL TO TRACK MYOCARDIAL MOTION USING ECHOCARDIOGRAPHY

  • Ahn, Chi Young
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.2
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    • pp.181-192
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    • 2014
  • In this paper, we propose a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frame from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, dropout or shadowing phenomena of cardiac walls. The proposed method deals with this shape distortion problem and reflects the motion realistic LV shape by applying global deformation modeled as affine transform partitively to the contour. We partition the tracking points on the contour into a few groups and determine each affine transform governing the motion of the partitioned contour points. To compute the coefficients of each affine transform, we use the least squares method with equality constraints that are given by the relationship between the coefficients and a few contour points showing good tracking results. Many real experiments show that the proposed method supports better performance than existing methods.

Effects of the Sampling Time in Motion Controller Implementation for Mobile Robots (모바일 로봇 모션 제어에 있어 샘플링 시간의 효과)

  • Jang, Tae-Ho;Kim, Youngshik
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.4
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    • pp.154-161
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    • 2014
  • In this research we investigate motion controller performance for mobile robots according to changes in the control loop sampling time. As a result, we suggest a proper range of the sample time, which can minimize final posture errors while improving tracking capability of the controller. For controller implementation into real mobile robots, we use a smooth and continuous motion controller, which can respect robot's path curvature limitation. We examine motion control performance in experimental tests while changing the control loop sampling time. Toward this goal, we compare and analyze experimental results using two different mobile robot platforms; one with real-time control and powerful hardware capability and the other with non-real-time control and limited hardware capability.

A Study on Implementation of Motion Graphics Virtual Camera with AR Core

  • Jung, Jin-Bum;Lee, Jae-Soo;Lee, Seung-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.8
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    • pp.85-90
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    • 2022
  • In this study, to reduce the time and cost disadvantages of the traditional motion graphic production method in order to realize the movement of a virtual camera identical to that of the real camera, motion graphics virtualization using AR Core-based mobile device real-time tracking data A method for creating a camera is proposed. The proposed method is a method that simplifies the tracking operation in the video file stored after shooting, and simultaneously proceeds with shooting on an AR Core-based mobile device to determine whether or not tracking is successful in the shooting stage. As a result of the experiment, there was no difference in the motion graphic result image compared to the conventional method, but the time of 6 minutes and 10 seconds was consumed based on the 300frame image, whereas the proposed method has very high time efficiency because this step can be omitted. At a time when interest in image production using virtual augmented reality and various studies are underway, this study will be utilized in virtual camera creation and match moving.

Non-Prior Training Active Feature Model-Based Object Tracking for Real-Time Surveillance Systems (실시간 감시 시스템을 위한 사전 무학습 능동 특징점 모델 기반 객체 추적)

  • 김상진;신정호;이성원;백준기
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.23-34
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    • 2004
  • In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

Realization of a Motion-based Interactive System Using Extraction of Real-time Search Terms

  • Lim, Sooyeon;Lee, Dongin
    • International Journal of Contents
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    • v.12 no.2
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    • pp.31-36
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    • 2016
  • The purpose of this research is to realize interactive art based on user's motions information using real time internet search terms. For this purpose, real-time search terms and related news information were extracted from three domestic and foreign portal sites, and the extracted information was used to generate content for interaction with the user. For interaction between the generated content and the user, a motion-based interactive technology that optimizes the intentions and experiences of the user was developed. A motion-based interactive system can be used to develop an immersive interface that induces user interest.

Tracking and Interaction Based on Hybrid Sensing for Virtual Environments

  • Jo, Dongsik;Kim, Yongwan;Cho, Eunji;Kim, Daehwan;Kim, Ki-Hong;Lee, Gil-Haeng
    • ETRI Journal
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    • v.35 no.2
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    • pp.356-359
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    • 2013
  • We present a method for tracking and interaction based on hybrid sensing for virtual environments. The proposed method is applied to motion tracking of whole areas, including the user's occlusion space, for a high-precision interaction. For real-time motion tracking surrounding a user, we estimate each joint position in the human body using a combination of a depth sensor and a wand-type physical user interface, which is necessary to convert gyroscope and acceleration values into positional data. Additionally, we construct virtual contents and evaluate the validity of results related to hybrid sensing-based whole-body tracking of human motion methods used to compensate for the occluded areas.