We present an exploratory study in the context of digital film analysis inspecting and comparing five canonical movies by applying methods of computer vision. We extract one frame per second of each movie which we regard as our sample. As computer vision methods we explore image-based object detection, emotion recognition, gender and age detection with state-of-the-art models. We were able to identify significant differences between the movies for all methods. We present our results and discuss the limitations and benefits of each method. We close by formulating future research questions we plan to answer by applying and optimizing the methods.