Detecting facial expressions using the kinect camera
This dissertation reports and recapitulates the progress of author’s research work on “Detecting facial expressions using the Kinect camera” under the scrutiny of Professor Justin Dauwels. This project comprises of the prospect detection of human emotion using Kinect Version 2. In this part, brig...
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sg-ntu-dr.10356-695222023-07-04T15:48:00Z Detecting facial expressions using the kinect camera Kulandaivelu Giridharan Justin Dauwels School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering This dissertation reports and recapitulates the progress of author’s research work on “Detecting facial expressions using the Kinect camera” under the scrutiny of Professor Justin Dauwels. This project comprises of the prospect detection of human emotion using Kinect Version 2. In this part, brightness changes in face while heart contracts and expands is used for extraction of features. The latter part of project includes the methods and procedures to process raw data and detect emotions. The prime objective of this project is to initially gather reliable data for heart rate detection using Kinect Version 2. Following which, a well designated protocol shows the subject a blend of YouTube videos to induce different emotions including happy, sad and neutral. Finally, analysis will be performed using heart rate detection algorithms and Tinke to detect the emotion of the subject. In this project, other than Kinect V2, TInke and Wrist blood pressure monitor are used. The prime aim is to pin point the heart rate ranges that can be assigned to emotions and to methodize the use of Kinect V2 to detect the heart rates for each kind of human emotion. Master of Science (Computer Control and Automation) 2017-02-02T05:18:14Z 2017-02-02T05:18:14Z 2017 Thesis http://hdl.handle.net/10356/69522 en 61 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Kulandaivelu Giridharan Detecting facial expressions using the kinect camera |
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This dissertation reports and recapitulates the progress of author’s research work on
“Detecting facial expressions using the Kinect camera” under the scrutiny of Professor
Justin Dauwels. This project comprises of the prospect detection of human emotion using
Kinect Version 2. In this part, brightness changes in face while heart contracts and expands
is used for extraction of features. The latter part of project includes the methods and
procedures to process raw data and detect emotions.
The prime objective of this project is to initially gather reliable data for heart rate detection
using Kinect Version 2. Following which, a well designated protocol shows the subject a
blend of YouTube videos to induce different emotions including happy, sad and neutral.
Finally, analysis will be performed using heart rate detection algorithms and Tinke to
detect the emotion of the subject.
In this project, other than Kinect V2, TInke and Wrist blood pressure monitor are used.
The prime aim is to pin point the heart rate ranges that can be assigned to emotions and to
methodize the use of Kinect V2 to detect the heart rates for each kind of human emotion. |
author2 |
Justin Dauwels |
author_facet |
Justin Dauwels Kulandaivelu Giridharan |
format |
Theses and Dissertations |
author |
Kulandaivelu Giridharan |
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Kulandaivelu Giridharan |
title |
Detecting facial expressions using the kinect camera |
title_short |
Detecting facial expressions using the kinect camera |
title_full |
Detecting facial expressions using the kinect camera |
title_fullStr |
Detecting facial expressions using the kinect camera |
title_full_unstemmed |
Detecting facial expressions using the kinect camera |
title_sort |
detecting facial expressions using the kinect camera |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/69522 |
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1772826209951940608 |