• Title/Summary/Keyword: real time motion tracking

Search Result 234, Processing Time 0.024 seconds

Adaptive Position Controller Design of Electro-hydraulic Actuator Using Approximate Model Inversion (근사적 모델 역변환을 활용한 전기-유압 액추에이터의 적응 위치 제어기 설계)

  • Lee, Kyeong Ha;Baek, Seung Guk;Koo, Ja Choon
    • The Journal of Korea Robotics Society
    • /
    • v.11 no.2
    • /
    • pp.92-99
    • /
    • 2016
  • An electro-hydraulic actuator (EHA) is widely used in industrial motion systems and the increasing bandwidth of EHA position control is important issue. The model-inverse feedforward controller is known to extend the bandwidth of system. When the system has non-minimum phase (NMP) zeros, direct model inversion makes system unstable. To overcome this problem, an approximate model-inverse method is used. A representative approximate model inversion method is zero phase error tracking control (ZPETC). However, if zeros locate right half plane of z-plane, the approximate inverse model amplifies the high-frequency response. In this paper, to solve the problem of ZPETC, an adaptive model-inverse control is proposed. The adaptive algorithm updates feedforward term in real-time. The effectiveness of the proposed adaptive model-inverse position control strategy is verified by comparison with typical proportional-integral (PI) control and feedforward control by experiments. As a result, the proposed adaptive controller extends the bandwidth of EHA position control.

Smart Flying-Disc Monitoring System with IoT Technology (IoT 기술이 적용된 스마트 플라잉 디스크 모니터링 시스템 구축)

  • Lee, Jung-Chul;Jang, Young-Jong;Hwang, Tae-Ho
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.14 no.5
    • /
    • pp.991-1000
    • /
    • 2019
  • The flying-disc game has started since 1940. It has been spreading rapidly in Korea since 2007, mainly in elementary schools. Additionally, as sports science has been developed, research on flying discs has been continued to build a monitoring system for technological improvement and efficiency. In this paper, we acquire information on the user's flying-disc using 9-axis motion sensor and GPS. Then we propose a method for wireless transmission using Bluetooth 5.0. Specifically, the HW platform was designed and implemented not only to monitor a real-time data but also to compare and analyze rotational speed, flight trajectory, and a count of disc rotation through post-processing.

Development and Evaluation of the V-Catch Vision System

  • Kim, Dong Keun;Cho, Yongjoo;Park, Kyoung Shin
    • Journal of the Korea Society of Computer and Information
    • /
    • v.27 no.3
    • /
    • pp.45-52
    • /
    • 2022
  • A tangible sports game is an exercise game that uses sensors or cameras to track the user's body movements and to feel a sense of reality. Recently, VR indoor sports room systems installed to utilize tangible sports game for physical activity in schools. However, these systems primarily use screen-touch user interaction. In this research, we developed a V-Catch Vision system that uses AI image recognition technology to enable tracking of user movements in three-dimensional space rather than two-dimensional wall touch interaction. We also conducted a usability evaluation experiment to investigate the exercise effects of this system. We tried to evaluate quantitative exercise effects by measuring blood oxygen saturation level, the real-time ECG heart rate variability, and user body movement and angle change of Kinect skeleton. The experiment result showed that there was a statistically significant increase in heart rate and an increase in the amount of body movement when using the V-Catch Vision system. In the subjective evaluation, most subjects found the exercise using this system fun and satisfactory.

Fast Hough circle detection using motion in video frames (동영상에서 움직임을 이용한 빠른 허프 원 찾기)

  • Won, Hye-Min;Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
    • /
    • v.11 no.6
    • /
    • pp.31-39
    • /
    • 2010
  • The Generalized Hough Transform(GHT) is the most used algorithm for circle detection with high accuracy. However, it requires many computation time, because many different templates are applied in order to find circles of various size. In the case of circle detection and tracking in video, the classical approach applies GHT for each frame in video and thus needs much high processing time for all frames. This paper proposes the fast GHT algorithm in video, using two consecutive frames are similar. In the proposed algorithm, a change-driven method conducts GHT only when two consecutive frames have many changes, and trajectory-based method does GHT in candidate areas and with candidate radius using circles detected in a previous frame. The algorithm can reduce computation time by reducing the number of frames, the edge count, and the number of searching circles, as factors which affects the speed of GHT. Our experimental results show that the algorithm successfully detects circles with less processing time and no loss of accuracy in video acquisited by a fixed camera and a moving camera.

Moving Object Detection using Clausius Entropy and Adaptive Gaussian Mixture Model (클라우지우스 엔트로피와 적응적 가우시안 혼합 모델을 이용한 움직임 객체 검출)

  • Park, Jong-Hyun;Lee, Gee-Sang;Toan, Nguyen Dinh;Cho, Wan-Hyun;Park, Soon-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.47 no.1
    • /
    • pp.22-29
    • /
    • 2010
  • A real-time detection and tracking of moving objects in video sequences is very important for smart surveillance systems. In this paper, we propose a novel algorithm for the detection of moving objects that is the entropy-based adaptive Gaussian mixture model (AGMM). First, the increment of entropy generally means the increment of complexity, and objects in unstable conditions cause higher entropy variations. Hence, if we apply these properties to the motion segmentation, pixels with large changes in entropy in moments have a higher chance in belonging to moving objects. Therefore, we apply the Clausius entropy theory to convert the pixel value in an image domain into the amount of energy change in an entropy domain. Second, we use an adaptive background subtraction method to detect moving objects. This models entropy variations from backgrounds as a mixture of Gaussians. Experiment results demonstrate that our method can detect motion object effectively and reliably.

Anomalous Event Detection in Traffic Video Based on Sequential Temporal Patterns of Spatial Interval Events

  • Ashok Kumar, P.M.;Vaidehi, V.
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.9 no.1
    • /
    • pp.169-189
    • /
    • 2015
  • Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

A Real-Time Head Tracking Algorithm Using Mean-Shift Color Convergence and Shape Based Refinement (Mean-Shift의 색 수렴성과 모양 기반의 재조정을 이용한 실시간 머리 추적 알고리즘)

  • Jeong Dong-Gil;Kang Dong-Goo;Yang Yu Kyung;Ra Jong Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.42 no.6
    • /
    • pp.1-8
    • /
    • 2005
  • In this paper, we propose a two-stage head tracking algorithm adequate for real-time active camera system having pan-tilt-zoom functions. In the color convergence stage, we first assume that the shape of a head is an ellipse and its model color histogram is acquired in advance. Then, the min-shift method is applied to roughly estimate a target position by examining the histogram similarity of the model and a candidate ellipse. To reflect the temporal change of object color and enhance the reliability of mean-shift based tracking, the target histogram obtained in the previous frame is considered to update the model histogram. In the updating process, to alleviate error-accumulation due to outliers in the target ellipse of the previous frame, the target histogram in the previous frame is obtained within an ellipse adaptively shrunken on the basis of the model histogram. In addition, to enhance tracking reliability further, we set the initial position closer to the true position by compensating the global motion, which is rapidly estimated on the basis of two 1-D projection datasets. In the subsequent stage, we refine the position and size of the ellipse obtained in the first stage by using shape information. Here, we define a robust shape-similarity function based on the gradient direction. Extensive experimental results proved that the proposed algorithm performs head hacking well, even when a person moves fast, the head size changes drastically, or the background has many clusters and distracting colors. Also, the propose algorithm can perform tracking with the processing speed of about 30 fps on a standard PC.

Eye Tracking Using Neural Network and Mean-shift (신경망과 Mean-shift를 이용한 눈 추적)

  • Kang, Sin-Kuk;Kim, Kyung-Tai;Shin, Yun-Hee;Kim, Na-Yeon;Kim, Eun-Yi
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.44 no.1
    • /
    • pp.56-63
    • /
    • 2007
  • In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and con-nected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based tex-ture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a 'aligns games.' The results show that the system process more than 30 frames/sec on PC for the $320{\times}240$ size input image and supply a user-friendly and convenient access to a computer in real-time operation.

An accuracy analysis of Cyberknife tumor tracking radiotherapy according to unpredictable change of respiration (예측 불가능한 호흡 변화에 따른 사이버나이프 종양 추적 방사선 치료의 정확도 분석)

  • Seo, jung min;Lee, chang yeol;Huh, hyun do;Kim, wan sun
    • The Journal of Korean Society for Radiation Therapy
    • /
    • v.27 no.2
    • /
    • pp.157-166
    • /
    • 2015
  • Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

  • PDF

A Robust Algorithm for Tracking Feature Points with Incomplete Trajectories (불완전한 궤적을 고려한 강건한 특징점 추적 알고리즘)

  • Jeong, Jong-Myeon;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.37 no.6
    • /
    • pp.25-37
    • /
    • 2000
  • The trajectories of feature points can be defined by the correspondences between points in consecutive frames. The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. The trajectories of feature points are determined by calculating the matching measure, which is defined as the minimum weighted Euclidean distance between two feature points. The weights are automatically updated in order to properly reflect the motion characteristics. We solve the correspondence problem as an optimal graph search problem, considering that the existence of false feature points may have serious effect on the correspondence search. The proposed algorithm finds a local optimal correspondence so that the effect of false feature point can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O($m^2n$) in the worst case, where m and n arc the number of feature points in two consecutive frames. By considering false feature points and by properly reflecting motion characteristics, the proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

  • PDF