Study of the Changing Trends in Facial Expression Recognition

Ravi, Sunitha; Mahima, S.

doi:10.5120/2509-3397

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…Bayesian technique has been used as an important static method. Ravi et al, [5], gave a comparative study and analysis of 'Facial Expression Recognition Technology' along with its progressive growth and developments. Oliveira et al, [4], proposed a novel method called two-dimensional discriminant locality preserving projections (2D-DLPP) is proposed that can best discriminate different pattern classes.…”

Section: Related Workmentioning

confidence: 99%

Performance comparisons of artificial neural network algorithms in facial expression recognition

Ahmed

Mohammed

Yahia

2015

IJET

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This paper presents methods for identifying facial expressions. The objective of this paper is to present a combination of texture oriented method with dimensional reduction and use for training the Single-Layer Neural Network (SLN), Back Propagation Algorithm (BPA) and Cerebellar Model Articulation Controller (CMAC) for identifying facial expressions. The proposed methods are called intelligent methods that can accommodate for the variations in the facial expressions and hence prove to be better for untrained facial expressions. Conventional methods have limitations that facial expressions should follow some constraints. To achieve the expression detection accuracy, Gabor wavelet is used in different angles to extract possible textures of the facial expression. The higher dimensions of the extracted texture features are further reduced by using Fisher's linear discriminant function for increasing the accuracy of the proposed method. Fisher's linear discriminant function is used for transforming higher-dimensional feature vector into a twodimensional vector for training proposed algorithms. Different facial emotions considered are angry, disgust, happy, sad, surprise and fear are used. The performance comparisons of the proposed algorithms are presented.

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Section: Related Workmentioning

confidence: 99%

Performance comparisons of artificial neural network algorithms in facial expression recognition

Ahmed

Mohammed

Yahia

2015

IJET

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Digital Technology for Natyashastra’s "Rasa" Measurement to Interpret Online Learning Engagement

Wavre,

Kuknor,

Dhaktod

2023

2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)

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Technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem

Lalithamani

Sabrigiriraj

2014

MG&V

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Template security of biometric systems is a vital issue and needs critical focus. The importance lies in the fact that unlike passwords, stolen biometric templates cannot be revoked. Hence, the biometric templates cannot be stored in plain format and needs strong protection against any forgery. In this paper, we present a technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem. Here, initially the input images are pre-processed using various processes to make images fit for further processing. In our proposed method, the features are extracted from the processed face and palm vein images by finding out unique common points. The chaff points are added to the already extracted points to obtain the combined feature vector. The secret key points which are generated based on the user key input (by using proposed method) are added to the combined feature vector to have the fuzzy vault. For decoding, the multi-modal biometric template from palm vein and face image is constructed and is combined with the stored fuzzy vault to generate the final key. Finally, the experimentation is conducted using the palm vein and face database available in the CASIA and JAFFE database. The evaluation metrics employed are FMR (False Match Ratio) and GMR (Genuine Match Ratio). From the metric values obtained for the proposed system, we can infer that the system has performed well.

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Study of the Changing Trends in Facial Expression Recognition

Cited by 3 publications

References 33 publications

Performance comparisons of artificial neural network algorithms in facial expression recognition

Performance comparisons of artificial neural network algorithms in facial expression recognition

Digital Technology for Natyashastra’s "Rasa" Measurement to Interpret Online Learning Engagement

Technique to generate face and palm vein-based fuzzy vault for multi-biometric cryptosystem

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