Automatic Caption Generation from Images Based on Facial Emotions
G. Priyanka1, T. Revathi2, K. Muneeswaran3
1G. Priyanka, Assistant Professor Senior Grade, Department of CSE, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
2T. Revathi, Professor Head, Department of IT, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
3K. Muneeswaran, Professor Head, Department of CSE, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
Manuscript received on 19 January 2020 | Revised Manuscript received on 02 February 2020 | Manuscript Published on 05 February 2020 | PP: 116-121 | Volume-8 Issue-4S5 December 2019 | Retrieval Number: D10381284S519/2019©BEIESP | DOI: 10.35940/ijrte.D1038.1284S519
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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: In the current era, the vast number of internet users accesses the social network sites like Facebook, Whatsapp, Twitter, and Instagram for uploading their images. User may upload all kind of images with different emotions. In this research article, we introduce novel facial emotion recognition technique using Convolutional Neural Network (CNN) approach and associated a caption automatically based on the identified emotion. We consider only still images for emotion classification. Using face detection algorithms faces were detected from the facial image which is followed by emotion prediction. We automated this detection process for images having frontal faces. In images having non-frontal faces, we manually plot the eye points for rotating the face in such a way that algorithm can detect faces easily. Inferences obtained as a result of experiments shows that the proposed work is capable of identifying minute differences between different emotions and predict accordingly. Based on the emotions identified corresponding captions are generated with better accuracy.
Keywords: Caption, Convolutional Neural Networks, Emotions, Facial Images.
Scope of the Article: Image Security