• Pankaj
• Er. Sumit Dalal

Face mining is characterized as the revelation of picture designs in a given gathering of pictures. It is an exertion that generally attracts upon information PC vision, picture handling, information mining, AI, database, and man-made reasoning. Facial acknowledgment breaks down and thinks about the examples from the facial pictures. Facial component extraction is a programmed acknowledgment of human faces by recognizing its highlights for example eyes, eyebrows and lips. In this paper, we are assessing the execution of PCA, GMM, GLCM and SVM to perceive seven distinctive outward appearances of two people, for example, cheerful, unbiased, and furious, nauseate, dismal, dread and astonishment. Our point is to speak to best systems which work best for facial acknowledgment. The present investigation demonstrates the plausibility of outward appearance acknowledgment for viable applications like reconnaissance and human PC communication.

EMOTION DETECTION FROM FACE USING PCA, GLCM, GMM and SVM

"EMOTION DETECTION FROM FACE USING PCA, GLCM, GMM and SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.765-771, June-2019, Available :http://www.jetir.org/papers/JETIR1906D22.pdf

"EMOTION DETECTION FROM FACE USING PCA, GLCM, GMM and SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp765-771, June-2019, Available at : http://www.jetir.org/papers/JETIR1906D22.pdf