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Facial Feature Extraction Based on Improved Harris Corner Detection Algorithm by Bagherian, Elhaam

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Feature-based face recognition system using utilized artificial neural network by Chai, Tong Yuen

“…The main contributions of this project are the automatic algorithms for mouth detection, facial features cropping and face classification. …”
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Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian by Saffian, Norhafizah

“…The facial expression consists of three steps that are face detection, facial feature extraction, and classification of feature extraction. …”
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Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

“…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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3D face registration across pose variation and facial expression using cross profile alignment by Anuar, Laili Hayati

“…The experiment conducted on challenging 3D face databases yields good results with 94.77% detection rate for the nose tip region detection algorithm. …”
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Automatic detection of face and facial features by Chai, Tong Yuen, Mohd Rizon, Mohamed Juhari, Prof. Dr., Woo, San San, Sugisaka, M.

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Computational stylometric model for oath and oath-like expressions in Quranic text by Alqurneh, Ahmad

“…This work proposes an oath-like expression detection algorithm (OLEDA) to develop a computational stylometric model for oaths based on stylometric applicationspecific features which are structural and content-specific features. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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A feature-based approach for segmenting faces by Zaqout, I., Zainuddin, R., Baba, S.

“…The algorithm detects feature points from the image and groups them into face candidates using geometric and grey level constraints. …”
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Anger Detection in Monitoring Drivers’ Facial Expression using Mobile App by Ee, Min Jie

“…This is because vibrating steering wheel can be caused by faulty brakes, wheel alignment and punctured tires. In order to detect driver’s angry facial expression, image processing algorithm will be applied and implemented in this project. …”
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Designing an expressive virtual Kompang on mobile device with tri-axial accelerometer by Leng, Hoo Yong, Mohd Norowi, Noris, Jantan, Azrul Hazri

“…Result from the study showed that the feature extraction algorithm had an accuracy of 86.78% at detecting drum hit at its peak acceleration value. …”
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Feature extraction and classification stage on facial expression : A review by Shidiq, Muchamad Bachram, Ernawan, Ferda, Khubrani, Mousa Mohammed, Nugroho, Fajar Agung

“…Human facial recognition involves face detection, feature extraction, and classification. …”
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A Bayesian probability model for Android malware detection by Sharfah Ratibah, Tuan Mat, Mohd Faizal, Ab Razak, Mohd Nizam, Mohmad Kahar, Juliza, Mohamad Arif

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Performance analysis for facial expression recognition under salt and pepper noise with median filter approach by Idris, Azrini

“…In face recognition, the simple process of face recognition system should go through image data retrieval, face detection, facial feature extraction and face recognition. …”
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A Bayesian probability model for Android malware detection by Sharfah Ratibah, Tuan Mat, Mohd Faizal, Ab Razak, Mohd Nizam, Mohmad Kahar, Juliza, Mohamad Arif, Ahmad Firdaus, Zainal Abidin

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The importance of data classification using machine learning methods in microarray data by Jaber, Aws Naser, Moorthy, Kohbalan, Machap, Logenthiran, Safaai, Deris

“…The detection of genetic mutations has attracted global attention. several methods have proposed to detect diseases such as cancers and tumours. …”
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Driver drowsiness detection system through facial expression using Convolutional Neural Networks (CNN) / Nipa Das Gupta, Rajesvary Rajoo and Patricia Jayshree Jacob by Gupta, Nipa Das, Rajoo, Rajesvary, Jacob, Patricia Jayshree

“…After processing the dataset, we extracted a wide range of features, which we fed into a deep convolutional neural network (CNN) algorithm. …”
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The application of Hough Transform for corner detection by Jamaludin, Mohad Fuad

“…As simple lines can be expressed using only one parameter, Hough Transform can detect them quickly. …”
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SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING by Heng, Elvin Jia Guang

“…This project aims to apply machine learning techniques to detect suicidal tendency from written text. Several machine learning algorithms and feature engineering techniques are studied and experimented to find out how they perform on the task of classifying texts into suicidal or non-suicidal texts.…”
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Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM) by Iqtait, M., Mohamad, F.S., Mamat, M.

“…Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. …”
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