With each passing day, new technologies are introduced to humans, bringing them closer to computers and forming a strong bond between them. Image processing is a boon to the world in today's technological age. In the realm of image processing, many research fields have emerged, such as mood detection, object detection, signature detection, and so on, with mood detection emerging as the most popular research area today. The most delicate way to interpret a human's mind, as well as a human's demand, is through facial expression. A human's desire, such as watching a movie, may be predicted using this facial expression, which saves consumers time and effort in looking through a movie list. This paper represents an approach of movie recommendation based on mood detection that employs a couple of neural networks such as CNN, VGGNet, Inception, MobileNet, and DenseNet. These neural networks can recognize facial expressions and can also propose movies based on this information. At last, we compare the results of our datasets to the results of the collected datasets.

This work has been published in International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies (ICAECT 2022).

Doi: 10.1109/ICAECT54875.2022.9807654

Cite as:

@INPROCEEDINGS{9807654, author={Elias, Tahasin and Rahman, Umma Saima and Ahamed, Kazi Afrime}, booktitle={2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)}, title={Movie Recommendation Based on Mood Detection using Deep Learning Approach}, year={2022}, volume={}, number={}, pages={1-6}, doi={10.1109/ICAECT54875.2022.9807654}}