Shot Change and Stuck Pixel Detection of Digital Video Assets
In this paper, we address two significant components of typical post-production workflows in current entertainment industry: (a) shot change detection and (b) dead- or stuck-pixel detection. The former involves identifying precise temporal boundaries of cinematographic content in order to analyze quality of cuts, while the latter is useful for localizing and correcting spatial anomalies that emerge during the image acquisition step due to faulty sensors. To address the aforementioned, we devise two novel data-driven approaches and demonstrate their portability, scalability, and efficacy through two respective cloud computing-based implementations. Our approaches show promising results on our in-house data set of a large number of movie titles indicating their effectiveness.
- Print ISSN
- 1545-0279
- Electronic ISSN
- 2160-2492
- Published
- 2018-07
- Content type
- Original Research
- Keywords
- Automated/semiautomated content quality control, dead-pixel detection, nonparametric machine learning, outlier detection, post-production workflow, shot-change detection
- DOI
- 10.5594/JMI.2018.2827278