Abstract: A system and method for predictive editorial sequencing of a directed video stream. A communication device receives candidate video streams captured by distributed camera devices. A computing platform determines, from the candidate video streams, a current temporal state of a real-world event by classifying the event into event phase classifications, and generates a temporal progression model predicting a forthcoming temporal state transition based on the current temporal state and historical phase progression data. The computing platform pre-determines transition windows derived from the temporal progression model, computes predicted narrative contribution scores for each candidate video stream representing alignment with the forthcoming temporal state, and generates a directed output video stream by selecting the candidate stream with the highest predicted narrative contribution score and executing transitions within the pre-determined transition windows.

Abstract: A system and method for the automated generation of a directed video stream from a plurality of distributed camera devices. Video streams captured by devices across multiple locations or users are transmitted via a communication network to a computing platform. The platform analyzes the streams to determine editorial selection decisions including stream selection, transition timing, and presentation ordering based on stream characteristics, predefined rules, or a trained machine learning model. A directed output video stream is generated by applying these decisions to the received streams. The computing platform may be implemented via mobile, edge, or cloud-based systems.

Abstract: Systems and methods for automated creative video direction are disclosed. A communication device receives a plurality of video streams from a plurality of video capture devices and at least one of at least one audio stream and telemetry data from a telemetry data source. A computing device processes the received data to extract at least one of a visual contextual feature, an audio contextual feature, and a telemetry contextual feature, and combines at least two of these features to generate a unified contextual representation of a common real-world occurrence. Based on the unified contextual representation, the computing device determines one or more editorial decisions, including at least one of selecting a video stream for presentation, determining transition timing, selecting a camera angle, or determining a transition behavior. The computing device outputs a directed output video stream by applying the editorial decisions to the plurality of video streams.

Abstract: A system and method for automated arbitration between multiple simultaneous video streams capturing a common real-world occurrence are provided. The system determines a temporal narrative state of the occurrence and computes, for each candidate video stream, a marginal contribution value relative to a currently selected output stream based on contextual divergence. A redundancy penalty is determined based on contextual similarity. A composite arbitration score is generated using at least the marginal contribution value and the redundancy penalty, and a competitive comparison of composite arbitration scores is performed to select a candidate stream for output.