ANN based human facial expression recognition in color images

Borah, Sagarika; Konwar, Sharmila

doi:10.1109/ichpca.2014.7045337

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…The human facial expression recognition method based on ANN is proposed in [7]. This is the automatic technique that detects 22 important facial feature points and generates facial feature vector by using Euclidian distances between particular points.…”

Section: Human Emotionsmentioning

confidence: 99%

“…Sometimes background of image might contain skin like pixels [24]. But this is not the interested region.…”

Section: Face Detectionmentioning

confidence: 99%

“…Total 18 feature points are used, as shown in above figure 5. For each image frame, feature vector is generated, which contains 9 feature elements [7]. Distance between two pixels or two feature points of image is calculated by using Euclidian Distance [31].…”

Section: Feature Extractionmentioning

confidence: 99%

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Human Affect Recognition System based on Survey of Recent Approaches

Malwatkar¹,

Sugandhi²,

Mahajan³

2017

IJCA

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In recent years, the analysis of human affective behavior has been a point of attraction for many researchers. Such automatic analysis is useful in various fields such as psychology, computer science, linguistics, neuroscience etc. Such affective computing is responsible for developing standard systems and devices, useful for recognition and interpretation of various human faces and gestures. The emotions are categories as anger, disgust, fear, happiness, sadness and surprise. Such emotion recognition system involves three main steps: face detection, feature extraction and facial expression classification. Hence, there is a need for standard approaches that solve the problem of machines understanding the human affect behavior. This survey paper presents some recent approaches that recognize the human affective behavior, with their advantages and limitations. This paper also presents some basic classifiers such as SVM, ANN, KNN and HMM, used for emotion classification and audiovisual databases with their emotion categories. Based on the survey, an affect recognition system has been proposed that adopts a cognitive semi-supervised approach.

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Section: Human Emotionsmentioning

confidence: 99%

“…Sometimes background of image might contain skin like pixels [24]. But this is not the interested region.…”

Section: Face Detectionmentioning

confidence: 99%