Timelines - Introduction
The play Video Intelligence Platform's Timeline function offers a sophisticated approach to video editing by utilizing advanced AI capabilities. This function is designed to handle complex multi-camera, multi-object setups, making it easier to generate organized and editable timelines. Here, we provide a detailed introduction to how the Timeline function works and what to expect from the AI-generated suggestions.
Compatible Non-Linear Editors (NLEs)
The play Video Intelligence Platform supports exporting timelines to formats compatible with various Non-Linear Editors (NLEs), ensuring seamless integration into your existing workflow. The compatible NLEs include:
- Adobe Premiere Pro: Export timelines in XML or EDL formats for easy import into Adobe Premiere Pro, a widely-used professional video editing software.
- Apple Final Cut Pro X: Generate FCP XML files compatible with Final Cut Pro X, allowing for advanced editing and finishing on macOS.
- Avid Media Composer: Utilize AAF and EDL formats to integrate with Avid Media Composer, a leading tool for film and television post-production.
- DaVinci Resolve: Export timelines in XML or AAF formats for use in DaVinci Resolve, known for its powerful color grading and post-production capabilities.
- Sony Vegas Pro: Use EDL or XML formats to bring your timelines into Sony Vegas Pro for further editing and effects.
- Other OTIO-Compatible Editors: Leverage the OpenTimelineIO (OTIO) JSON format for compatibility with any editor that supports OTIO, offering a flexible and standardized interchange format.
By supporting these widely-used NLEs, the play Video Intelligence Platform ensures that your AI-generated timelines can be easily transferred and edited in the software of your choice.
How It Works
AI-Driven Suggestions
The AI in the play Video Intelligence Platform analyzes the ingested video content to provide several key suggestions:
- Object Detection and Tracking: Identifies and tracks objects and subjects across multiple video feeds.
- Scene Detection and Ranking: Detects significant scenes based on object interactions and ranks them according to their importance.
- Action Recognition: Recognizes specific actions and activities within the video, adding context to the detected scenes.
- Automatic Framing and Editing: Suggests framing adjustments and basic edits, such as aspect ratio adaptation, visual effects, and initial cuts.
Metadata Generation
For each video, the AI generates a comprehensive metadata layer that includes:
- Recognized Actions and Activities: Detailed information about identified actions, such as movements, interactions, and significant events.
- Transcribed Speech: Text transcriptions of any spoken content within the video, aiding in content searchability and accessibility.
- Timecodes and Cut Marks: Precise timestamps and cut points for each detected action and scene, facilitating easier navigation and editing.
- Additional Metadata: Tags, labels, and other relevant information that enhance the video’s context and usability.
This metadata is stored within a structured container, making it easy to access and query via the platform’s API.
Timeline Assembly
The platform assembles the detected scenes, actions, and metadata into a coherent and structured timeline. This timeline serves as a foundation for further editing and refinement, providing a clear sequence of events and actions that editors can build upon.
Exporting and Timeline Structure
The generated timelines can be exported in various industry-standard formats, ensuring compatibility with popular video editing software. For detailed guides on how to export a generated timeline and understand the structure of a timeline, refer to the following documentation: