Detecting facial expressions from kinect camera

In the past years, there were several advances methodology regarding face detection and tracking, features extraction methodology and techniques used for expression classification. Detection of facial expression is a very common communication method between computer and human interface. The facial b...

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Main Author: Muhammad Hafiz Bin Mohd Zakee
Other Authors: Justin Dauwels
Format: Final Year Project
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/68282
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-682822023-07-07T16:34:31Z Detecting facial expressions from kinect camera Muhammad Hafiz Bin Mohd Zakee Justin Dauwels School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation In the past years, there were several advances methodology regarding face detection and tracking, features extraction methodology and techniques used for expression classification. Detection of facial expression is a very common communication method between computer and human interface. The facial behaviour according to emotion is an important element in human communication, as it carries an amazing amount of information that can reflect emotional feelings. Observing person’s facial expressions or behaviours assist a person understand their emotional feelings. New technology provided today for detecting facial expressions, with rapid and high resolution image acquisition, helps us to analyse and recognize in real time facial expressions. This application can be useful in many real time applications like military security, trading (the customer’s emotions about a product), patient monitoring, and others. This paper presents an application that detects three main basic facial expression (Neutral, Happy and Sad) by using Microsoft Kinect for Windows sensor V1. To detect the facial expressions, facial parameterization using Facial Action Coding System (FACS) were extracted from the recording by face tracking SDK provided by Microsoft Kinects. Four FACS trained annotators were employed to manually label the facial expressions by viewing a videotaped recording of 11 subject’s facial behaviours from Kinect Studio. A machine learning algorithm, KNN and Decision Tree will classify the facial expression sin real time. Bachelor of Engineering 2016-05-25T05:04:11Z 2016-05-25T05:04:11Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68282 en Nanyang Technological University 82 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
Muhammad Hafiz Bin Mohd Zakee
Detecting facial expressions from kinect camera
description In the past years, there were several advances methodology regarding face detection and tracking, features extraction methodology and techniques used for expression classification. Detection of facial expression is a very common communication method between computer and human interface. The facial behaviour according to emotion is an important element in human communication, as it carries an amazing amount of information that can reflect emotional feelings. Observing person’s facial expressions or behaviours assist a person understand their emotional feelings. New technology provided today for detecting facial expressions, with rapid and high resolution image acquisition, helps us to analyse and recognize in real time facial expressions. This application can be useful in many real time applications like military security, trading (the customer’s emotions about a product), patient monitoring, and others. This paper presents an application that detects three main basic facial expression (Neutral, Happy and Sad) by using Microsoft Kinect for Windows sensor V1. To detect the facial expressions, facial parameterization using Facial Action Coding System (FACS) were extracted from the recording by face tracking SDK provided by Microsoft Kinects. Four FACS trained annotators were employed to manually label the facial expressions by viewing a videotaped recording of 11 subject’s facial behaviours from Kinect Studio. A machine learning algorithm, KNN and Decision Tree will classify the facial expression sin real time.
author2 Justin Dauwels
author_facet Justin Dauwels
Muhammad Hafiz Bin Mohd Zakee
format Final Year Project
author Muhammad Hafiz Bin Mohd Zakee
author_sort Muhammad Hafiz Bin Mohd Zakee
title Detecting facial expressions from kinect camera
title_short Detecting facial expressions from kinect camera
title_full Detecting facial expressions from kinect camera
title_fullStr Detecting facial expressions from kinect camera
title_full_unstemmed Detecting facial expressions from kinect camera
title_sort detecting facial expressions from kinect camera
publishDate 2016
url http://hdl.handle.net/10356/68282
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