Search Results - (( motion detection method algorithm ) OR ( using estimation method algorithm ))
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An evaluation of optical flow algorithms for crowd analytics in surveillance system
Published 2017“…This paper presents an overview of the optical flow methods that used mainly for pedestrian and crowd motion detection. …”
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Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…The results of three experiments demonstrate that our algorithm substantially outperforms all previous methods. …”
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A comparison study on different crowd motion estimation algorithms using matlab
Published 2014“…This article describes different motion detection methods, gives a brief illustration of the optical flow conception, and presents in details the Lucas-Kanade and Horn-Schunk algorithms for optical flow estimation and their implementation using MATLAB. …”
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Investigation of block matching algorithm for video coding
Published 2013“…Then, the best BMA algorithm technique will be chosen to develop a hybrid method that varies with the motion type of the video. …”
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Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar
Published 2017“…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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Improved abnormal detection using self-adaptive social force model for visual surveillance
Published 2017“…For both indoor and outdoor scene, the proposed algorithm outperforms the other methods with accuracy 97% and 100%. …”
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Detection and Classification of Moving Objects for an Automated Surveillance System
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Detection and classification of moving objects for an automated surveillance system
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…The performance results obtained using two publicly available datasets showed significant improvement over baseline methods in the detection of specific activity details and reduced error rate. …”
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Adaptive template matching of photoplethysmogram pulses to detect motion artefact
Published 2018“…Objective: The photoplethysmography (PPG) signal, commonly used in the healthcare settings, is easily affected by movement artefact leading to errors in the extracted heart rate and SpO 2 estimates. …”
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Detection and classification of moving objects for an automated surveillance system
Published 2006“…Technically, this method estimate the motion area before updates the background by taking a weighted average of non-motion area of the current background altogether with non-motion area of the current frame of the video sequence. …”
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13
Human upper body pose region estimation
Published 2013“…The tracking the HUB pose is based on the face detection algorithm. Our evaluation was done mainly using 50 images from INRIA Person Dataset.…”
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Book Chapter -
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Blind motion image deblurring using canny edge detector with generative adversarial networks / Idriss Moussa Idriss
Published 2021“…Experiment s are conducted using the GoPro dataset. The proposed combined method has achieved good deblurring with edge-preserving results based on the evaluation metrics used. …”
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Crowd behavior monitoring using self-adaptive social force model
Published 2019“…Instead of using any segmentation methods, the motion of particles in each frame is captured by particle advection method. …”
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Capture and estimate the speed of the object for remote monitoring / Nor Sajidah Ab Ghani
Published 2016“…The optical flow used Kanade Lucas Algorithm method to track the vehicle movement in the video. …”
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Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon
Published 2020“…Upon using the artifact detection method followed by BP estimation, the SBP and DBP were improved in BHS grades from D to A. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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19
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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