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Project 10 Facial Emotion Recognition Based On Mouth Analysis SSIP 08, Vienna 1

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Presentation on theme: "Project 10 Facial Emotion Recognition Based On Mouth Analysis SSIP 08, Vienna 1"— Presentation transcript:

1 Project 10 Facial Emotion Recognition Based On Mouth Analysis SSIP 08, Vienna 1 http://www.we-hope-project10-will-win.info

2 The Project Objective : To recognize emotional state / expression using mouth information Input: Mouth images (no make-up) Output: Emotional State/ Expression Happy, Neutral, Sad 2 http://www.we-hope-project10-will-win.info

3 The Team 3 Kornél programmer Kornél programmer Péter Web programmer Péter Web programmer Kamal programmer Kamal programmer Naiem researcher Naiem researcher Sofia programmer Sofia programmer http://www.we-hope-project10-will-win.info

4 The Tasks Create facial expressions photographic database Segment the mouth in the input image Use suitable features for expression characterization Design a reliable classifier to distinguish between different mouth expressions 4 http://www.we-hope-project10-will-win.info

5 SSIP Lips database Happy, Neutral and Sad Photos of SSIP students and lecturers Thank you all!!! Happy Neutral Sad 5 http://www.we-hope-project10-will-win.info

6 Mouth Segmentation 6 Input ImageHSV Space - Hue Thresholding Morphological Operations http://www.we-hope-project10-will-win.info

7 Segmentation Results… And Segmentation Problems… 7 http://www.we-hope-project10-will-win.info

8 Lips Features Extraction Detect the leftmost and rightmost lip points Normalize images (rotation, translation and scaling) Calculate features Eccentricity Convex Area Minor Axis Ratio of Upper to Lower Lip 8 http://www.we-hope-project10-will-win.info

9 Expression Classification SVM Classifier Two Stage Classification Mouth Features  ☺ 9 http://www.we-hope-project10-will-win.info

10 Results 1 Differences between different classes were found to be statistically significant (p<0.01) Classification Accuracy Stage 1 (Sad / Not Sad)  88% Stage 2 (Happy/ Neutral)  62% 10 http://www.we-hope-project10-will-win.info

11 Results 2 11 http://www.we-hope-project10-will-win.info

12 Future Work Acquire larger database for training and testing Test different facial expressions (such as anger and disgust) Other classifiers: NN, FIS Conclusion Mouth information is often insufficient for recognizing facial expression / emotional state Other face features such as eyes and eyebrows can contribute in emotional state recognition 12 http://www.we-hope-project10-will-win.info

13 GUI 13 http://www.we-hope-project10-will-win.info

14 References M. Gordan, C. Kotropoulos, I. Pitas, “ Pseudoautomatic Lip Contour Detection Based on Edge Direction Patterns” J. Kim, S. Na, R. Cole, “ Lip Detection Using Confidence-Based Adaptive Thresholding” F. Tang, “ Facial Expression Recognition using AAM and Local Facial Features” M. Pantic, M. Tomc, L. Rothkrantz, “ A Hybrid Approcah to Mouth Features Detection ” 14 http://www.we-hope-project10-will-win.info

15 Thank you for your attention!!! 15 http://www.we-hope-project10-will-win.info


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