Managing video metadata poses a significant challenge for the audiovisual sector. In recent years, audiovisual production, distribution, and consumption have increased exponentially, making it essential to properly handle metadata to maximize the utility of each file.
What is Video Metadata?
Video metadata comprises data describing important information about a video file, including each of its frames and scenes. These metadata play a crucial role in asset management, allowing us to identify technical details of the file (location, format, duration, size, date, etc.) as well as information within each frame (people, locations, audio, texts, etc.).
Undoubtedly, managing video metadata is a challenge as these informational tags assist in archiving and locating the desired clips or frames.
What are the Benefits of Proper Video Metadata Management?
The main benefits of agile and structured video metadata management include:
- Facilitating technical production by ensuring video specifications match when selecting clips for editing or distribution.
- Streamlining the search process by identifying clips based on themes, visual elements, emotional content through AI-driven media analysis, and spoken content through AI-based voice detection.
- Automating scheduling by filling spaces with assets based on series, timeline, theme, subject, genre, demographics, or any other metric.
- Aligning advertising with content consistently, optimizing monetization.
- Categorizing audiovisual assets according to rights permissions and access certificates.
- Providing automated voice-to-text and subtitles with time codes.
- Simplifying the creation of strategic reports, offering performance information.
Easily Manage Your Video Metadata with Our MAM VSNExplorer
At VSN, we are aware of the importance of metadata in content management. In our Media Asset Management (MAM) system, VSNExplorer, we process metadata for images, audio, and video throughout the entire workflow, ensuring seamless integration into each system. User-generated metadata input is fully customizable, and whenever possible, predictive or automated workflows are incorporated to expedite and enhance the metadata categorization process.
Artificial Intelligence: Revolutionizing Video Metadata Management
Traditionally, metadata generation was primarily a manual task, involving the viewing of countless hours of video. Now, API integration with AI engines in our MAM VSNExplorer automates this management, transforming months of cataloging into mere minutes.
- Recognize faces, objects, locations, organizations, and logos, among other elements.
- Identify different layers of audio (music, voice, speakers, sound effects).
- Convert voice to text.
- Perform automatic translations.
- Conduct optical character recognition (OCR).
- Analyze sentiments, enabling the automatic detection of emotions within a video.
In the long run, metadata serves to optimize processes and improve return on investment. Contact our team and discover how you can maximize the potential of your video metadata.
Subscribe to our newsletter