Analyzing Movie Posters using DBSCAN Technique Procedia Computer Science - Phonglorpisit, Sutthichet; Wongpattararoj, Boonyakeat; Pridiyanon, Pawanon; Limprasert, Wasit; Marukatat, Sanparith (Rattanakosin Journal of Science and Technology, 2024)
This study uses Image Processing and Computer Vision techniques to analyze movie posters. It use Image Clustering and Image Augmentation to distinguish factors that influence the decision to watch a movie. The analysis uses DBSCAN and Resnet50 to classify data, and Dimension Reduction and Umap to reduce data size. The results of the analysis highlight the appeal of movie posters and indicate the factors that influence interest and decision-making in movie viewing. The survey and analysis results found that the characteristics of movie posters are significant in assisting viewers’ decision-making, making them more rational in choosing movies and increasing their satisfaction in watching movies.