Pre-Publication V3. The process of identifying the transitions between scenes, where a scene is defined as a continuous sequence of shots that take place in the same time and location (often with a relatively static set of characters) and share a common action or theme. (e.g. The automated analysis of content to group individual shots into larger units (“scenes”) based on their visual, audio, or textual data (e.g. time, location, and/or theme).
Deliberation Summary:
(1) Relationship of term to boundary detection, considering whether the latter should sit beneath this entry as a sub-item or stand as a distinct editorial process. (2) Term concerns grouping footage into broader units, while boundary detection concerns the precise points at which continuity breaks.
Pre-Publication V2. AI Scene Segmentation
The automated process of identifying the transitions between scenes, where a scene is defined as a continuous sequence of shots that take place in the same time and location (often with a relatively static set of characters) and share a common action or theme. For example, automatically dividing a continuous film, raw shoot, or trailer into logical, meaningful narrative units (scenes and shots).
Deliberation Summary:
(1) Consider if term related to segmentation entry and all should carry AI in their titles. (2) Term describes a task-based outcome that can be accomplished through established workflows, as with several other entries in the list.
Pre-Publication V1. The automated process of identifying the transitions between scenes, where a scene is defined as a continuous sequence of shots that take place in the same time and location (often with a relatively static set of characters) and share a common action or theme. For example, automatically dividing a continuous film, raw shoot, or trailer into logical, meaningful narrative units (scenes and shots).