Cutting the Frame: An In-Depth Look at the Hitchcock Computer Vision Dataset

Abstract

This paper presents a comprehensive dataset comprising annotations generated by the Google Vision API for approximately 105,000 frames extracted from 15 Alfred Hitchcock films. These annotations include information about object detection, facial recognition, web-entity analysis, and explicit content filtering. With potential applications in the digital humanities and film studies, this dataset enables researchers to not only explore and evaluate cinematic content but also the ways that it resurfaces in various cultural contexts online. The paper provides a detailed account of the dataset creation process, which involved the decryption of the DVD, frame extraction, and costs of annotations. Additionally, the paper outlines future research possibilities based on the dataset. These include statistical analysis of frame content and labels to identify patterns and trends, comparisons of different computer vision algorithms to assess their accuracy and effectiveness, and the utilization of bipartite networks to explore mise-en-scene in films.

Keywords

• film studies
• digital humanities
• visual turn
• computer vision
• network analysis