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THE EXTENDED COHN-KANADE DATASET(CK+):A COMPLETE DATASET FOR ACTION UNIT AND EMOTION- SPECIFIED EXPRESSION Author : Patrick Lucey, Jeffrey F. Cohn, Takeo.

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Presentation on theme: "THE EXTENDED COHN-KANADE DATASET(CK+):A COMPLETE DATASET FOR ACTION UNIT AND EMOTION- SPECIFIED EXPRESSION Author : Patrick Lucey, Jeffrey F. Cohn, Takeo."— Presentation transcript:

1 THE EXTENDED COHN-KANADE DATASET(CK+):A COMPLETE DATASET FOR ACTION UNIT AND EMOTION- SPECIFIED EXPRESSION Author : Patrick Lucey, Jeffrey F. Cohn, Takeo Kanade, Jason Saragih, Zara Ambadar Conference on Computer Vision and Pattern Recognition 2010 Speaker : Liu, Yi-Hsien 1

2 Outline Introduction The CK+ Dataset Emotion Labels Baseline System Experiments Conclusion 2

3 Introduction In 2000, the Cohn-Kanade (CK) database was released Automatically detecting facial expressions has become an increasingly important research area 3

4 Introduction(Cont.) The CK database contains 486 sequences across 97 subjects. Each of the sequences contains images from onset (neutral frame) to peak expression (last frame). The peak frame was reliably FACS(Facial Action Coding System ) coded for facial action units (AUs). 4

5 Introduction(Cont.) Facial Action Coding System (FACS) is a system to taxonomize human facial movements by their appearance on the face 5

6 Introduction(Cont.) While AU codes are well validated, emotion labels are not The lack of a common performance metric against which to evaluate new algorithms Standard protocols for common databases have not emerged 6

7 The CK+ Dataset Participants were 18 to 50 years of age, 69% female, 81% Euro-American, 13% Afro-American, and 6% other groups Image sequences for frontal views and 30-degree views were digitized into either 640x490 or 640x480 pixel arrays with 8- bit gray-scale or 24-bit color values. 7

8 The CK+ Dataset(Cont.) For the CK+ distribution, they have augmented the dataset further to include 593 sequences from 123 subjects (an additional 107 (22%) sequences and 26 (27%) subjects). For the 593 posed sequences, full FACS coding of peak frames is provided. 8

9 Emotion Labels They included all image data from the pool of 593 sequences that had a nominal emotion label based on the subject’s impression of each of the 7 basic emotion categories: Anger, Contempt, Disgust, Fear, Happy, Sadness and Surprise. 9

10 Emotion Labels(Cont.) 1. Compared the FACS codes with the Emotion Prediction Table from the FACS 2. After the first pass, a more loose comparison was performed 3. The third step involved perceptual judgment of whether or not the expression resembled the target emotion category. 10

11 Emotion Labels(Cont.) 11

12 Emotion Labels(Cont.) As a result of this multistep selection process, 327 of the 593 sequences were found to meet criteria for one of seven discrete emotions. 12

13 Baseline System 13

14 Baseline System(Cont.) Active Appearance Models (AAMs) The shape s of an AAM is described by a 2D triangulated mesh. In particular, the coordinates of the mesh vertices define the shape s = [x1; y1; x2; y2; …. ; xn; yn] 14

15 Baseline System(Cont.) SPTS : The similarity normalized shape, refers to the 68 vertex points for both the x- and y- coordinates, resulting in a raw 136 dimensional feature vector CAPP : The canonical normalized appearance, refers to where all the shape variation has been normalized with respect to the base shape 15

16 Baseline System(Cont.) SVMs(Support Vector Machines) attempt to find the hyper plane that maximizes the margin between positive and negative observations for a specified class. 16

17 Experiments Emotion detection. To maximize the amount of training and testing data, they believe the use of a leave-one-subject-out cross- validation configuration should be used. 17

18 Experiments(Cont.) SPTS 18

19 Experiments(Cont.) CAPP 19

20 Experiments(Cont.) SPTS+CAPP 20

21 Conclusion In this paper, they try to address those three issues by presenting the Extended Cohn-Kanade (CK+) database Added another 107 sequences as well as another 26 subjects. The peak expression for each sequence is fully FACS coded and emotion labels have been revised and validated 21

22 Conclusion(Cont.) Propose the use of a leave-one-out subject cross- validation strategy for evaluating performance Present baseline results on this using our Active Appearance Model (AAM)/support vector machine (SVM) system. 22


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