Transformation of Facial Expression into Corresponding Emoticons
Ankur Ankit1, Dhananjay Narayan2, Alok Kumar3
1Ankur Ankit, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Dhananjay Narayan, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Alok Kumar, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 256-258 | Volume-8 Issue-5, June 2019 | Retrieval Number: E6892068519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are many different ways to express and communicate our feelings. The two classified ways of communication are verbal and non – verbal. Facial expressions are a great way of communication involving the exchange of wordless intimations. It has enticed much research attention in the field of computer vision and Artificial intelligence. Many kinds of research have been done for grouping these expressions. It is chiefly done to acquire the sentiments of humans. In this project, an API can be employed to fetch images from any camera-based application in real time. HAAR cascade classifier is employed to extract the image features from the images fetched earlier. Support Vector Machines (SVM) is used to classify those features into corresponding expressions. And these expressions are then converted to their equivalent emojis, after that these emojis are get superimposed over the actual face expression as a mask. This project can be used to study the different facial expressions that a machine can understand and also it can be used as a filter used in social media apps like Facebook, Instagram, Snapchat, etc.
Keywords: Emotion Recognition, Face Detection API, SVM, HAAR, OpenCV, Emoji, Computer Vision
Scope of the Article: Pattern Recognition