GDL

Journal from gdlhub / 2018-08-21 10:56:32
By : Suja Palaniswamy, Shikha Tripathi, STIKOM Dinamika Bangsa Jambi
Created : 2018-08-07, with 1 files

Keyword : classification; emotion; facial expression; feature extraction; illumination; pose; Raspberry Pi II.
Url : http://journals.itb.ac.id/index.php/jictra/article/view/3479
Document Source : WEB

A technique for emotion recognition from facial expressions in images with simultaneous pose, illumination and age variation in real time is proposed in this paper. The basic emotions considered are anger, disgust, happy, surprise,and neutral. Feature vectors that were formed from images from the CMUMultiPIE database for pose and illumination were used for training the classifier.For real-time implementation, Raspberry Pi II was used, which can be placed ona robot to recognize emotions in interactive real-time applications. Theproposed method includes face detection using Viola Jones Haar cascade, Active Shape Model (ASM) for feature extraction, and AdaBoost for classification in realtime. Performance of the proposed method was validated in real time by testing with subjects from different age groups expressing basic emotions with varying pose and illumination. 96% recognition accuracy at an average time of 120 ms was obtained. The results are encouraging, as the proposed method gives better accuracy with higher speed compared to existing methods from the literature. The major contribution and strength of the proposed method lie in marking suitable feature points on the face, its speed and invariance to pose, illumination and age in real time.

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