Movie Recommendation Based on Mood Detection using Deep Learning Approach

Abstract

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.