Post on 15-Jan-2017
FACIAL EXPRESSION RECOGNITION BASED ON
IMAGE FEATURE
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
ANWESHA PAULID: 110206
TASNIM TARANNUMID: 110216
PRESENTED BY:
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Overview
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Facial Expression & Facial Expression Recognition Related Works Problems Of Existing System Motivation Proposed Method Conclusion Reference
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Facial Expression
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Powerful, natural and immediate means for human to communicate their emotions.
Vital part of communication.
Widely recognized in social interaction.
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Facial Expression contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Neutral Happy Surprise Sad Disgust Angry Fear
Fig 1: Basic Facial Expression.
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Expression Recognition
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Locating faces in the scene. Extracting facial features.
Analyzing the motion of facial feature.
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Expression Recognition contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Face Acquisition
Facial Data Extraction &
Representation
Facial Expression Recognition
Face Detection
Head Pose
Estimation
Feature-based
Appearance-based
Frame-based
Sequence-based
Fig 2: Basic Structure of Facial Expression Recognition.
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Related Work
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Reference Image Acquisition
Feature Extraction Classification Recognition
Performance
Neeta Sarode et al.[1]
Gray scale image to recognize four expressions
2D appearance-based local approach
Euclidean distance
Accuracy rate 81%
Rupinder Saini et al.[2]
PCA, Gabor wavelet, PCA with SVD
Euclidean distance, PCA
[1] Neeta Sarode, Prof. Shalini Bhatia, “Facial Expression Recognition”, (IJCSE) International Journal on Computer Science and Engineering, Vol. 02, No. 05, 2010.
[2] Rupinder Saini, Narinder Rana, “Facial Expression Recognition Techniques, Database & Classifiers”, International Journal of Advances in Computer Science and Communication Engineering (IJACSCE), Vol. 2, Issue 2, June 2014.
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Related Work contd..
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Reference Image Acquisition
Feature Extraction Classification Recognition
Performance
Jeemoni Kalita et al.[3]
60 samples with various expression of RGB color image
Manually extracted and Eigenvector based distributed feature
Euclidean distance
Recognition rate 95% & process time 0.0295 sec
Ajit P.Gosavi et al.[4]
Real database image to recognize five basic emotions
PCA (Principal Component analysis) with SVD (Singular Value Decomposition)
Euclidean distance
Avg. accuracy 89.70% & avg. recognition rate 65.42%
[3] Jeemoni Kalita, Karen Das, “Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 2, 2013.[4] Ajit P.Gosavi and S.R. Khot, “Facial Expression Recognition uses Principal Component Analysis with Singular Value Decomposition”, International Journal of Advance Research in Computer Science and Management Studies Vol. 1, Issue 6, November 2013.
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Related Work contd..
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Reference Image Acquisition
Feature Extraction Classification Recognition
Performance
Akshat Garget et al.[7]
Gray scale image
PCA (Principal Component analysis)
Euclidean distance & PCA
Accuracy rate 89.0%
Mahesh Kumbhar et al.[8]
JAFFE [6] database image
PCA(Principal Component analysis), Gabor wavelet
Euclidean distance
Recognition rate 60% to 70%
[
7] Akshat Garg, Vishakha Choudhary, “Facial Expression Recognition Using Principal Component Analysis”, International Journal of Scientific Research Engineering &Technology (IJSRET), Vol. 1 Issue4, July 2012.
[8] Mahesh Kumbhar, Ashish Jadhav, Manasi Patil, “Facial Expression Recognition Based on Image Feature”, International Journal of Computer and Communication Engineering, Vol. 1, No. 2, July 2012.
[6] JAFFE (Japanese Female Facial Expression) Face Database. Available: [Online] http:// www.kasrl.org/jaffe.html
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Problems Of Existing System
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Don’t contain enough feature points
PCA-based face recognition systems are hard to scale up
Color image burdensome[1] Neeta Sarode, Prof. Shalini Bhatia, “Facial Expression Recognition”, (IJCSE) International Journal on Computer Science and Engineering, Vol. 02, No. 05, 2010.
[4] Ajit P.Gosavi and S.R. Khot, “Facial Expression Recognition uses Principal Component Analysis with Singular Value Decomposition”, International Journal of Advance Research in Computer Science and Management Studies Vol. 1, Issue 6, November 2013.
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Problems Of Existing System contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Cropping manually is time killing
Inabilities (different angles and different reasons).
[3] Jeemoni Kalita, Karen Das, “Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 2, 2013.
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Motivation
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Recognize facial expression as like a human.
Recognize six basic expressions.
Increase the accuracy rate.
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Proposed Method
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Block diagram of proposed system:
Image Acquisition
Feature Extraction
Classifier
Happy SadSurpriseAngryFearDisgust
Fig 3: Block diagram.
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Proposed Method contd….
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Image Acquisition: Convert the color image into gray scale
image.
Fig 4: RGB- color image converted into gray scale
image.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Feature Extraction:• Gaussian filter.
• Radial Symmetry Transform.
Fig 5: application of Gaussian filter.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Feature Extraction:
• Edge projection.
• Segmentation using Laplacian of Gaussian operator at zero threshold.
.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Classifier:• Euclidean distance based on
geometrical relationship.
• The feature vector V.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Classifier: Here, Vd0 = distance of eyebrow,Vd1 = distance between right eyebrow and nose tip,Vd2 = distance between left eyebrow and nose,Vw = mouth width,Vh = mouth height,Vul = upper lip curvature,Vll = lower lip curvature.
Fig 6: Geometrical parameters of the face, forming the
feature vector.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Decision Making Techniques:
• Feature vector calculation.
• Observe each component of feature vector.
• Comparison between testing image and neutral image.
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Proposed Method contd…
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Result Analysis:
Comparison between the testing image with it’s corresponding images from training database [6].
[6] JAFFE (Japanese Female Facial Expression) Face Database. Available: [Online] http://
www.kasrl.org/jaffe.html
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Conclusion
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Recognize six basic facial expressions.
Future work: Will develop the same in real time videos.
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Reference
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
[1] Neeta Sarode, Prof. Shalini Bhatia, “Facial Expression Recognition”, (IJCSE) International Journal on Computer Science and Engineering, Vol. 02, No. 05, 2010.
[2] Rupinder Saini, Narinder Rana, “Facial Expression Recognition Techniques, Database & Classifiers”, International Journal of Advances in Computer Science and Communication Engineering (IJACSCE), Vol. 2, Issue 2, June 2014.
[3] Jeemoni Kalita, Karen Das, “Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 2, 2013.
[4] Ajit P.Gosavi and S.R. Khot, “Facial Expression Recognition uses Principal Component Analysis with Singular Value Decomposition”, International Journal of Advance Research in Computer Science and Management Studies Vol. 1, Issue 6, November 2013.
[6] JAFFE (Japanese Female Facial Expression) Face Database. Available: [Online] http:// www.kasrl.org/jaffe.html
[7] Akshat Garg, Vishakha Choudhary, “Facial Expression Recognition Using Principal Component Analysis”, International Journal of Scientific Research Engineering &Technology (IJSRET), Vol.
1 Issue4, July 2012.
[8] Mahesh Kumbhar, Ashish Jadhav, Manasi Patil, “Facial Expression Recognition Based on Image Feature”, International Journal of Computer and Communication Engineering, Vol. 1, No. 2, July 2012.
COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY
Thank you.