Search Results - (( motion estimation method algorithm ) OR ( features selection method algorithm ))

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  1. 1

    Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

    Published 2016
    “…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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    Thesis
  2. 2

    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
    “…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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    Article
  3. 3

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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  4. 4

    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

    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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  5. 5

    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
  6. 6

    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
  7. 7

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

    Published 2021
    “…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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  8. 8

    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
  9. 9
  10. 10

    ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES by KAJO, IBRAHIM

    Published 2015
    “…Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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    Thesis
  11. 11

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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    Book Chapter
  12. 12

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

    Published 2012
    “…Simulation result shows that as compared to previous research, this algorithm achieves up to average 60% reduction in motion estimation time without degrading the video quality.…”
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    Thesis
  13. 13

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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  14. 14

    New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique by Hamid, Nurul 'Atiqah

    Published 2016
    “…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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  15. 15
  16. 16

    An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

    Published 2018
    “…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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    Article
  17. 17

    An adaptive block-based matching algorithm for crowd motion sequences by Kajo, I., Kamel, N., Malik, A.S.

    Published 2018
    “…For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. …”
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    Article
  18. 18

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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    Thesis
  19. 19

    An evaluation of optical flow algorithms for crowd analytics in surveillance system by Kajo, I., Malik, A.S., Kamel, N.

    Published 2017
    “…The improvement in computational efficiency and increasing interest in robust and accurate motion estimation algorithms lead to increase in the use of optical flow in crowd analytic applications. …”
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    Article
  20. 20

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

    Published 2011
    “…Simulation result shows that compared to Full Search (FS), this algorithm achieves up to 60% reduction in motion estimation time without degrading the video quality.…”
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    Conference or Workshop Item