Search Results - (( (emotion OR motion) detection system algorithm ) OR ( level classification system 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
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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  5. 5
    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
    “…To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. …”
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  6. 6
    Vader lexicon and support vector machine algorithm to detect customer sentiment orientation

    Vader lexicon and support vector machine algorithm to detect customer sentiment orientation by Vivine Nurcahyawati, ., Zuriani, Mustaffa

    Published 2023
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  7. 7
    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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  8. 8
    WEBCAM MOTION DETECTION USINGVISUAL BASIC

    WEBCAM MOTION DETECTION USINGVISUAL BASIC by Abdullah, Ilyana

    Published 2005
    “…Watch Eyes Motion Detection System is aproject used to enhance student's interest in multimedia system development, but at the same time the project can be used as motion detection system that will help any person in doing research in motion detection purposes. …”
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  9. 9
    Web Camera Application For Motion Detection

    Web Camera Application For Motion Detection by Koay, Su Yeong

    Published 2003
    “…The new method to detect motion is "vision motion detection". It is the artificial way of machine vision system compared to human's vision in detecting motion. …”
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  10. 10
    Vehicle Monitoring System Using Motion Detection Algorithms For USM Campus.

    Vehicle Monitoring System Using Motion Detection Algorithms For USM Campus. by Osman, Mohd. Azam, Talib, Abdullah Zawawi, Tan, Kian Lam, Wong, Poh Lee, Sabudin, Maziani

    Published 2007
    “…With the possible introduction of the motion detection and character recognition algorithms in security systems of the future, vehicle identities such as license plate numbers can be captured and processed at the security post to make it possible for the vehicles to be monitored remotely. …”
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  11. 11
    Real-time system for facial emotion detection using GPSO algorithm

    Real-time system for facial emotion detection using GPSO algorithm by Bashir, Mohammed Ghandi, R., Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  12. 12
    Study of machine learning in computer vision using Raspberry Pi

    Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

    Published 2024
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  13. 13
    Facial emotion detection using GPSO and Lucas-Kanade algorithms

    Facial emotion detection using GPSO and Lucas-Kanade algorithms by Bashir, Mohammed Ghandi, Nagarajan, Ramachandran, Prof. Dr., Hazry, Desa, Prof. Madya Dr.

    Published 2010
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  14. 14
    Human Spontaneous Emotion Detection System

    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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  15. 15
    Vision-based flame analysis using motion and Edge Detection

    Vision-based flame analysis using motion and Edge Detection by Razmi, Suzilawati Mohd, Saad, Nordin, Asirvadam, Vijanth Sagayan

    Published 2010
    “…This paper stresses on the flame detection algorithm. The results show that detection of flame using motion amp; shape features can be achieved by using Background Subtraction and Edge Detection approach.…”
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  16. 16
    HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM

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

    Published 2019
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  17. 17
    Development of a flexible video analysis system for motion detection and alarm generation

    Development of a flexible video analysis system for motion detection and alarm generation by Shafie, Amir Akramin, Ali, Md. Hazrat, Hafiz, Fadhlan, Mat Ali, Roslizar

    Published 2010
    “…The system will trigger alarm once the motion is detected and when it exceeds the desire threshold value. © 2010 IEEE.…”
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  18. 18
    An FPGA based embedded vision system for real-time motion detection

    An FPGA based embedded vision system for real-time motion detection by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

    Published 2015
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  19. 19
    Real-time measurement and gait detection algorithm for motion control of active ankle foot orthosis / Aminuddin Hamid

    Real-time measurement and gait detection algorithm for motion control of active ankle foot orthosis / Aminuddin Hamid by Hamid, Aminuddin

    Published 2015
    “…This thesis proposes a real time gait phase detection system to control AAFO for rehabilitation and assist ankle motion. …”
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  20. 20
    Motion detection using Horn-Schunck optical flow

    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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