Search Results - motion extraction ((((method algorithm) OR (sensor algorithm))) OR (bat algorithm))

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  1. 1

    Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

    Published 2019
    “…The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. …”
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    Article
  2. 2

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…First, to investigate existing multi-sensor and automatic feature extraction methods for human activity detection and health monitoring using motion sensor. …”
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    Thesis
  3. 3
  4. 4

    Finger Application Using K-Curvature Methods and Kinect Sensor in Real-time by MM. Zabri, Abu Bakar, Rosdiyana, Samad, Pebrianti, Dwi, Mahfuzah, Mustafa, Nor Rul Hasma, Abdullah

    Published 2015
    “…İn this paper, the proposed method is to detect and recognizes the fingertips by using the K-Curvature algorithm. …”
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    Conference or Workshop Item
  5. 5

    Real-time Rotation Invariant Hand Tracking Using 3D Data by Rosdiyana, Samad, M. Zabri, Abu Bakar, Pebrianti, Dwi, Nicolaas Lim, Yong Aan

    Published 2014
    “…This paper proposes hand tracking method using hand tracker algorithm released by NiTE, hand’s segmentation method, hand contour detection and center of palm detection. …”
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    Conference or Workshop Item
  6. 6

    Human activity and posture classification using smartphone sensors and Matlab mobile by Jamian, Syahirah, Gunawan, Teddy Surya, Kartiwi, Mira, Ahmad, Robiah, Kadir, Kushairy, Nordin, Muhammad Noor

    Published 2022
    “…Motion signals from three subjects are measured, data is preprocessed using a filtering technique, features are extracted, feature normalization is used to reduce bias in data measurement, and activities are classified. …”
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    Proceeding Paper
  7. 7

    A vision-based deep learning approach for non-contact vibration measurement using (2+1)D CNN and optical flow by Harold Harrison, Mazlina Mamat, Farah Wong, Hoe Tung Yew, Racheal Lim, Wan Mimi Diyana Wan Zaki

    Published 2025
    “…An optical flow-based preprocessing algorithm synchronized motion features in recorded video inputs with measured vibration labels, improving measurement accuracy. …”
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    Article
  8. 8

    Fast adaptive motion estimation search algorithm for H.264 encoder by Patwary, Md Anwarul Kaium

    Published 2012
    “…Motion estimation is a technique of video compression and video processing applications; it extracts motion information from the video sequence. …”
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    Thesis
  9. 9

    HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM by LO , TIMOTHY YIN HONG

    Published 2019
    “…In a human detection, the software is represented by algorithms, in which algorithm also being used in the process of training the dataset. …”
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    Final Year Project
  10. 10

    Pothole detection using multispectral sensor and unmanned aerial vehicle imagery / Muhammad Hafiz Aizuddin Mohd Zaidi by Mohd Zaidi, Muhammad Hafiz Aizuddin

    Published 2024
    “…The study has three objectives: to evaluate the accuracy of 3D pothole estimations from UAV images compared to actual pothole data, to investigate the impact of multispectral band combinations on pothole edge detection, and to assess different algorithms for pothole area extraction using multispectral and visible images. …”
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    Thesis
  11. 11

    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
  12. 12

    Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

    Published 2022
    “…Human Activity Recognition (HAR) focuses on detecting people's daily regular activities based on time-series recordings of their actions or motions. Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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    Proceeding
  13. 13
  14. 14

    Development of an economic wireless human motion analysis device for quantitative assessment of human body joint by Ong, Zhi Chao, Seet, Y.C., Khoo, Shin Yee, Noroozi, Siamak

    Published 2018
    “…Currently there are many camera or active sensor based motion analysis systems available on the market. …”
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    Article
  15. 15

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

    Published 2012
    “…This system is design to detect motion in a crowd using one of the optical flow algorithms, Horn-Schunck method. …”
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    Conference or Workshop Item
  16. 16

    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
  17. 17

    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

    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
  19. 19

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

    Published 2006
    “…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. 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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    Thesis
  20. 20

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

    Published 2006
    “…Moving object is detected by using combination of two frame differencing and adaptive image averaging with selectivity. 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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    Thesis