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Fig 1.

General flow diagram for a typical facial expression recognition (FER) system.

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Fig 2.

(a) shows the dependency graph of HMM, while (b) presents the dependency graph of MEMM.

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Fig 3.

MEMM based on expression state model for FER system.

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Table 1.

Recognition rate of the proposed FER system using CK+ dataset of facial expressions (Unit: %).

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Table 1 Expand

Table 2.

Recognition rate of the proposed FER system using JAFFE dataset of facial expressions (Unit: %).

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Table 2 Expand

Table 3.

Recognition rate of the proposed FER system using MUG dataset of facial expressions (Unit: %).

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Table 3 Expand

Table 4.

Recognition rate of the proposed FER system using USTC-NVIE dataset of facial expressions (Unit: %).

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Table 5.

Recognition rate of the proposed FER system using IMFDB dataset of facial expressions (Unit: %).

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Table 6.

Recognition rate of the proposed FER system using AFEW dataset of facial expressions (Unit: %).

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Table 6 Expand

Fig 4.

3D-feature plot of the proposed FER system for the six facial expressions using CK+ dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 4 Expand

Fig 5.

3D-feature plot of the proposed FER system for the six facial expressions using JAFFE dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 5 Expand

Fig 6.

3D-feature plot of the proposed FER system for the six facial expressions using MUG dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 6 Expand

Fig 7.

3D-feature plot of the proposed FER system for the six facial expressions using USTC-NVIE dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 7 Expand

Fig 8.

3D-feature plot of the proposed FER system for the six facial expressions using IMFDB dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 8 Expand

Fig 9.

3D-feature plot of the proposed FER system for the six facial expressions using AFEW dataset.

It can be seen that the system clearly classified the expressions classes.

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Fig 9 Expand

Table 7.

Confusion matrix of the proposed FER system that is trained on CK+ dataset and tested on JAFFE, MUG, USTC-NVIE, IMFDB, and AFEW datasets of facial expressions (Unit: %).

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Table 8.

Confusion matrix of the proposed FER system that is trained on JAFFE dataset and tested on CK+, MUG, USTC-NVIE, IMFDB, and AFEW datasets of facial expressions (Unit: %).

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Table 8 Expand

Table 9.

Confusion matrix of the proposed FER system that is trained on MUG dataset and tested on CK+, JAFFE, USTC-NVIE, IMFDB, and AFEW datasets of facial expressions (Unit: %).

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Table 9 Expand

Table 10.

Confusion matrix of the proposed FER system that is trained on USTC-NVIE dataset and tested on CK+, JAFFE, MUG, IMFDB, and AFEW datasets of facial expressions (Unit: %).

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Table 10 Expand

Table 11.

Confusion matrix of the proposed FER system that is trained on IMFDB dataset and tested on CK+, JAFFE, MUG, USTC-NVIE, and AFEW datasets of facial expressions (Unit: %).

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Table 11 Expand

Table 12.

Confusion matrix of the proposed FER system that is trained on AFEW dataset and tested on CK+, JAFFE, MUG, USTC-NVIE, and IMFDB datasets of facial expressions (Unit: %).

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Table 13.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using CK+ dataset of facial expressions (Unit: %).

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Table 13 Expand

Table 14.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using JAFFE dataset of facial expressions (Unit: %).

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Table 14 Expand

Table 15.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using MUG dataset of facial expressions (Unit: %).

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Table 15 Expand

Table 16.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using USTC-NVIE dataset of facial expressions (Unit: %).

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Table 16 Expand

Table 17.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using IMFDB dataset of facial expressions (Unit: %).

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Table 17 Expand

Table 18.

Confusion matrix of the proposed FER system with HMM (as a recognition model), instead of using the proposed recognition model (that is MEMM model) using AFEW dataset of facial expressions (Unit: %).

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Table 19.

Comparison results of the proposed FER system with the proposed MEMM model against some stat-of-the-art works (Unit: %).

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