Search Results - motion extraction ((path algorithm) OR (((bat algorithm) OR (based algorithm))))

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  1. 1

    Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

    Published 2011
    “…Algorithms have been developed for extracting these features after segmenting the head and the two hands. …”
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    Book Chapter
  2. 2

    Features extraction based on fuzzy clustering and segmentation onto the motion region for medium field surveillance application by Maliki, Mohamad Nansah, Abu Bakar Al-Attas, Syed Abdul Rahman

    Published 2004
    “…Incorporating the motion-based segmentation the complexity of the fuzzy clustering will also be reduced because only the motion region will be processed to the clustering algorithm.…”
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    Book Section
  3. 3

    A new search and extraction technique for motion capture data by Mohamad, Rafidei

    Published 2008
    “…Results from the experiments show that matching motion files were successfully extracted from the motion capture library using the new algorithm based on different human body segments.…”
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    Thesis
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    MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

    Published 2016
    “…The Particle Filtering (PF) algorithm is the most extensively used tor generative model based articulated human motion tracking. …”
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    Thesis
  6. 6

    Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…This paper presents an application of artificial neural network for the classification of single channel EMG signal in the context of hand motion detection. Seven statistical input features that are extracted from the preprocessed single channel EMG signals recorded for four predefined hand motions have been used for neural network classifier. …”
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    Article
  7. 7

    Application of image quality assessment module to motion-blurred wood images for wood species identification system by Rajagopal, Heshalini, Khairuddin, Anis Salwa Mohd, Mokhtar, Norrima, Ahmad, Azlin, Yusof, Rubiyah

    Published 2019
    “…A reliable motion deblurring technique, which is based on Lucy–Richardson algorithm, is employed to enhance the motion-blurred images before proceeding to the next stage, which is the feature extraction process. …”
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    Article
  8. 8

    Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

    Published 2017
    “…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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    Monograph
  9. 9

    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter by Nooralishahi, Parham, Loo, Chu Kiong, Shiung, Liew Wei

    Published 2019
    “…Moreover, we investigate the behavior of our algorithm under challenging conditions including the subject's motions and illumination variation, which shows that our algorithm can reduce the influences of illumination interference and rigid motions significantly. …”
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    Article
  10. 10

    Finger Motion In Classifying Offline Handwriting Patterns by Yeoh, Shen Horng

    Published 2017
    “…In previous studies, the offline handwriting classification is determined solely based on the handwriting patterns. To the best of our knowledge, no studies were found to predict the English words inclination based on the finger motions. …”
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    Monograph
  11. 11

    Motion detection using Horn-Schunck optical flow by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

    Published 2012
    “…By performing some appropriate feature extraction techniques, this system allows us to achieve better results in detecting motion and determining the velocity of that motion in order to analyze the human behaviour based on its velocities. …”
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    Conference or Workshop Item
  12. 12

    Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…The conventional and most effective time and timefrequency based features are extracted and normalized. The neural network has been trained with the normalized feature set with supervised learning method. …”
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    Article
  13. 13

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…Extracted time and time-frequency based feature sets are used to train the neural network. …”
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    Proceeding Paper
  14. 14

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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    Article
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    A method for motion tracking of ventricular endocardial surface by O. K. Rahmat, Rahmita Wirza, Dawood, Faten Abed Ali, Dimon, Mohd Zamrin, Kadiman, Suhaini, Abdullah, Lili Nurliyana

    Published 2014
    “…The present invention relates to a method for automatic motion tracking of ventricular endocardial surface in three dimensional (3D) echocardiography, characterized by the steps of extracting a plurality of ventricular endocardial contours over a complete cardiac cycle; identifying a plurality of landmarks on each ventricular endocardial contour; measuring displacement vector flow (DVF) for each landmark by comparing a pair of consecutive ventricular endocardial contours; measuring velocity vector flow (VVF) for each landmark from end-diastolic (ED) to end-systolic (ES) and vice versa; identifying at least four landmarks from the plurality of landmarks on each ventricular endocardial contour to represent anatomical landmarks of left lateral surface, right lateral surface, inferior wall and anterior wall by using geometrical distance calculation (GDC) algorithm; analysing ventricular endocardial motion direction using a fuzzy logic analyzer (FLA) for the four landmarks identified; updating values of the displacement vector flow (DVF) and velocity vector flow (VVF) based on the ventricular endocardial motion direction; and generating graphical curves of time versus values of the displacement vector flow (DVF) and velocity vector flow (VVF) for the four landmarks identified.…”
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    Patent
  18. 18

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The features extracted were then classified through three classical ML models, namely Support Vector Machine, k -Nearest Neighbour (k-NN) and Random Forest to determine the best pipeline for wink -based EEG signals. …”
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    Thesis
  19. 19

    Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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    Thesis
  20. 20

    Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

    Published 2006
    “…Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
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    Thesis