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Facial expression recognition based on image feature

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Tasnim Tara
Tasnim Tara

This is my pre- defence thesis presentation on facial expression recognition.

Présentations et discours publics
1  sur  23
FACIAL EXPRESSION RECOGNITION BASED ON IMAGE FEATURE COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY ANWESHA PAUL ID: 110206 TASNIM TARANNUM ID: 110216 PRESENTED BY:
LOGO2 Overview COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Facial Expression & Facial Expression Recognition  Related Works  Problems Of Existing System  Motivation  Proposed Method  Conclusion  Reference
LOGO3 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.
LOGO4 Facial Expression contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY Neutral Happy Surprise Sad Disgust Angry Fear Fig 1: Basic Facial Expression.
LOGO5 Expression Recognition COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Locating faces in the scene.  Extracting facial features.  Analyzing the motion of facial feature.
LOGO6 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.
LOGO7 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.
LOGO8 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.
LOGO9 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
LOGO10 Problems Of Existing System COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Don’t contain enough feature points.[1]  PCA-based face recognition systems are hard to scale up.[4]  Color image burdensome.[4] [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.
LOGO11 Problems Of Existing System contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Cropping manually is time killing.[3]  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.
LOGO12 Motivation COMPUTER SCIENCE & ENGINEERING  Recognize facial expression as like a human.  Recognize six basic expressions.  Increase the accuracy rate.
LOGO13 Proposed Method COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY Block diagram of proposed system: Image Acquisition Feature Extraction Classifier Happy Sad Surprise Angry Fear Disgust Fig 3: Block diagram.
LOGO14 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.
LOGO15 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Feature Extraction: • Gaussian filter. • Radial Symmetry Transform ∗. Fig 5: application of Gaussian filter.
LOGO16 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Feature Extraction: • Edge projection ∗. • Segmentation using Laplacian of Gaussian operator at zero threshold. .
LOGO17 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Classifier: • Euclidean distance based on geometrical relationship. • The feature vector V. 𝑉 = 𝑉𝑑0 𝑉𝑑1 𝑉𝑑2 𝑉𝑤 𝑉ℎ 𝑉𝑢𝑙 𝑉𝑙𝑙
LOGO18 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.
LOGO19 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.
LOGO20 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
LOGO21 Conclusion COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Recognize six basic facial expressions.  Future work: Will develop the same in real time videos.
LOGO22 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.

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Facial expression recognition based on image feature

  • 1. FACIAL EXPRESSION RECOGNITION BASED ON IMAGE FEATURE COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY ANWESHA PAUL ID: 110206 TASNIM TARANNUM ID: 110216 PRESENTED BY:
  • 2. LOGO2 Overview COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Facial Expression & Facial Expression Recognition  Related Works  Problems Of Existing System  Motivation  Proposed Method  Conclusion  Reference
  • 3. LOGO3 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.
  • 4. LOGO4 Facial Expression contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY Neutral Happy Surprise Sad Disgust Angry Fear Fig 1: Basic Facial Expression.
  • 5. LOGO5 Expression Recognition COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Locating faces in the scene.  Extracting facial features.  Analyzing the motion of facial feature.
  • 6. LOGO6 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.
  • 7. LOGO7 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.
  • 8. LOGO8 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.
  • 9. LOGO9 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
  • 10. LOGO10 Problems Of Existing System COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Don’t contain enough feature points.[1]  PCA-based face recognition systems are hard to scale up.[4]  Color image burdensome.[4] [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.
  • 11. LOGO11 Problems Of Existing System contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Cropping manually is time killing.[3]  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.
  • 12. LOGO12 Motivation COMPUTER SCIENCE & ENGINEERING  Recognize facial expression as like a human.  Recognize six basic expressions.  Increase the accuracy rate.
  • 13. LOGO13 Proposed Method COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY Block diagram of proposed system: Image Acquisition Feature Extraction Classifier Happy Sad Surprise Angry Fear Disgust Fig 3: Block diagram.
  • 14. LOGO14 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.
  • 15. LOGO15 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Feature Extraction: • Gaussian filter. • Radial Symmetry Transform ∗. Fig 5: application of Gaussian filter.
  • 16. LOGO16 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Feature Extraction: • Edge projection ∗. • Segmentation using Laplacian of Gaussian operator at zero threshold. .
  • 17. LOGO17 Proposed Method contd… COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Classifier: • Euclidean distance based on geometrical relationship. • The feature vector V. 𝑉 = 𝑉𝑑0 𝑉𝑑1 𝑉𝑑2 𝑉𝑤 𝑉ℎ 𝑉𝑢𝑙 𝑉𝑙𝑙
  • 18. LOGO18 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.
  • 19. LOGO19 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.
  • 20. LOGO20 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
  • 21. LOGO21 Conclusion COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY  Recognize six basic facial expressions.  Future work: Will develop the same in real time videos.
  • 22. LOGO22 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.
  • 23. COMPUTER SCIENCE & ENGINEERING KHULNA UNIVERSITY Thank you.