Search Results - (( motion estimation based algorithm ) OR ( level classification _ algorithm ))*

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  1. 1
    Detection and Classification of Moving Objects for an Automated Surveillance System

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

    Published 2006
    “…A completely automated system means a computer will perform the entire task from low level detection to higher level motion analysis. …”
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  2. 2
    Detection and classification of moving objects for an automated surveillance system

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

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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  3. 3
    Detection and classification of moving objects for an automated surveillance system

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

    Published 2006
    “…A completely automated system means a computer will perforin the entire task from low level detection to higher level motion analysis. …”
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  4. 4
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

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

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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  5. 5
    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition

    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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  6. 6
    Multi-sensor fusion based on multiple classifier systems for human activity identification

    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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  7. 7
    An Adaptive Motion Estimation Algorithm for Irregular Motion of Objects

    An Adaptive Motion Estimation Algorithm for Irregular Motion of Objects by Kajo, Ibrahim, Malik, Aamir Saeed, Kamel , Nidal

    Published 2014
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  8. 8
    ADAPTIVE MOTION ESTIMATION ALGORITHM FOR CROWDED SCENES

    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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  9. 9
    An adaptive block-based matching algorithm for crowd motion sequences

    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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  10. 10
    An adaptive block-based matching algorithm for crowd motion sequences

    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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  11. 11
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

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

    Published 2015
    “…Motion estimation is a technique to reduce high information redundancy which exists between successive frames in a video sequences. …”
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  12. 12
    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…In video coding, research is focused on the development of fast motion estimation (ME) algorithms while keeping the coding distortion as small as possible. …”
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  13. 13
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    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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  14. 14
    An adaptive motion estimation algorithm for irregular motion of objects

    An adaptive motion estimation algorithm for irregular motion of objects by Kajo, I., Malik, A.S., Kamel, N.

    Published 2014
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  15. 15
    Fast directional search algorithm for fractional pixel motion estimation for H.264 AVC

    Fast directional search algorithm for fractional pixel motion estimation for H.264 AVC by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun, Yap, Vooi Voon

    Published 2013
    “…Fractional pixel motion estimation (ME) is required to achieve more accurate motion vectors and higher compression efficiency. …”
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  16. 16
    New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique

    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
    “…Motion Estimation or ME is deemed as one of the effective and popular techniques in video compression. …”
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  17. 17
    Multilevel optimization for dense motion estimation

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…This research has been oriented towards the design of a new technique for fast and reliable dense motion estimation. We used variational models of optical flow computation to estimate the dense motion in a sequence of images.We have been interested in developing a multilevel optimization solver to produce accurate optical flow estimation for real-time applications.To the best of our knowledge, two-ways multilevel optimization techniques are used for the first time in the context of a computer vision problem. …”
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  18. 18
    Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm

    Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Beng Gan, Kok, Abd Aziz, Noor Azah, Huong, , Audrey, You, Huay Woon

    Published 2023
    “…Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits.…”
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  19. 19
    Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm

    Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm by Rahman, Md. Mahmudur, Gan, Kok Beng, Abd Aziz, Noor Azah, Huong, Audrey, Woon You, Huay

    Published 2023
    “…Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits.…”
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  20. 20
    Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter

    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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