Turkish Movie Genre Classification from Poster Images using Convolutional Neural Networks

Accessing to the best matching multimedia data is a trending topic due to the enormous amount of demand from people for movies, online TV series, videos etc. Advertising/Introducing form/image of such multimedia applications is important to give the key information to the audience. Sometimes a movie poster may play an important role to present the movie genre correctly. In recent years, Convolutional Neural Networks (CNN) as a deep learning architecture achieved state of-the- art performance in many image processing and recognition applications. In this paper, we implement transfer learning and fine-tuning methods on top of Google Inception-v3 algorithm, which is one of the most popular CNN architectures in this domain, and present comparative results of these methods in classifying the movie genre on a dataset consisting of Turkish movie posters. The obtained results show that fine tuning method performs better than pure CNN and transfer learning models on movie genre classification task.