• A Jahnavi
• Shaik Taj Mahaboob
• MSiva Kumar

Facial emotion recognition is becoming increasingly popular in a progressive research area and it plays a major role in Human-Computer-Interaction. In the real-world conditions, it faces many challenges, i.e., illumination changes, large pose variations and partial or full occlusions, which cause different facial areas with different sharpness and completeness. Inspired by this fact, Based on partial faces facial expression recognition is been focused. Here, we compare contribution of seven facial areas of low resolution images, including nose areas, mouth areas, eyes areas, nose to mouth areas, nose to eyes areas, mouth to eyes areas and the whole face areas. In this, we find that mouth regions contain much emotional information compared with nose areas and eyes areas through analysis on the confusion matrix and the class activation map. In Existing system it doesn’t identify exact emotion of a person. In this proposed algorithm we take the larger facial areas, hybrid extraction feature and CNN classification. In this paper we present literature survey to compare the efficiencies with Other Recognition Techniques with different approaches.

Facial emotion recognition, Facial areas, Class activation map, Confusion matrix

"A LITERATURE REVIEW ON REGION BASED ROBUST FACIAL EXPRESSION ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.301-304, March-2019, Available :http://www.jetir.org/papers/JETIRAK06057.pdf

"A LITERATURE REVIEW ON REGION BASED ROBUST FACIAL EXPRESSION ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp301-304, March-2019, Available at : http://www.jetir.org/papers/JETIRAK06057.pdf