Abstract: Provided are systems and methods for automatic video processing that employ machine learning models to process input video and understand user video content in a semantic and cultural context. This recognition enables the processing system to recognize interesting temporal events, and build narrative video sequences automatically, for example, by linking or interleaving temporal events or other content with film-based categorizations. In further embodiments, the implementation of the processing system is adapted to mobile computing platforms which can be distributed as an “app” within various app stores. In various example, the mobile apps turn everyday users into professional videographers. In further embodiments, music selection and dialog based editing can likewise be automated via machine learning models to create dynamic and professional quality video segments.

Abstract: Provided are systems and methods for automatic video processing that employ machine learning models to process input video and understand user video content in a semantic and cultural context. This recognition enables the processing system to recognize interesting temporal events, and build narrative video sequences automatically, for example, by linking or interleaving temporal events or other content with film-based categorizations. In further embodiments, the implementation of the processing system is adapted to mobile computing platforms which can be distributed as an “app” within various app stores. In various example, the mobile apps turn everyday users into professional videographers. In further embodiments, music selection and dialog based editing can likewise be automated via machine learning models to create dynamic and interest professional quality video segments.

Abstract: Provided are systems and methods for automatic video processing that employ machine learning models to process input video and understand user video content in a semantic and cultural context. This recognition enables the processing system to recognize interesting temporal events, and build narrative video sequences automatically, for example, by linking or interleaving temporal events or other content with film-based categorizations. In further embodiments, the implementation of the processing system is adapted to mobile computing platforms which can be distributed as an “app” within various app stores. In various example, the mobile apps turn everyday users into professional videographers. In further embodiments, music selection and dialog based editing can likewise be automated via machine learning models to create dynamic and interest professional quality video segments.