What is Video Intelligence
Video Intelligence - AI-powered analysis and understanding of video content at scale
Video intelligence refers to the use of AI and machine learning to automatically analyze, understand, and extract structured information from video content. This includes scene detection, object recognition, face identification, activity recognition, transcription, and temporal event analysis — transforming raw video files into searchable, actionable data.
How It Works
Video intelligence systems process videos by first splitting them into frames or scenes, then applying multiple AI models in parallel. Visual models detect objects, faces, and actions in each frame. Audio models transcribe speech and identify sounds. Temporal models understand how events unfold over time. The extracted information is indexed for search and downstream applications.
Technical Details
The pipeline typically involves scene boundary detection (using visual similarity thresholds), frame-level feature extraction (CNNs, vision transformers), temporal modeling (3D convolutions, video transformers), speech-to-text (Whisper), and metadata aggregation. Results are stored as time-indexed annotations linked to the source video for frame-accurate retrieval.
Best Practices
- Use scene detection to avoid redundantly processing similar consecutive frames
- Apply face deduplication to prevent the same person from appearing multiple times per scene
- Index both visual and audio features for comprehensive search
- Store timestamps with every extracted feature for frame-level retrieval
- Process videos asynchronously and use webhooks for completion notifications