Annotating video data requires different tools than static images. Objects move, occlude each other, change shape, and leave the frame. This tutorial covers video annotation on Datature Nexus, including frame-by-frame labeling, object interpolation, and video tracking tools that carry labels across frames automatically.
What This Tutorial Covers
- Uploading video files and navigating the video annotation timeline
- Drawing annotations on keyframes and letting Nexus interpolate between them
- Using video tracking to follow objects across frames automatically
- Managing object identities when targets leave and re-enter the frame
- Reviewing and correcting interpolated annotations
- Exporting video annotations for model training
Keyframe Interpolation vs. Frame-by-Frame
Labeling every frame of a 30fps video is impractical. A 2-minute clip has 3,600 frames. Datature's interpolation engine lets you annotate keyframes (every 10th, 20th, or 50th frame), then fills in the gaps by tracking object position and shape between your labeled frames. You review and correct the interpolated labels rather than drawing from scratch.
Who This Is For
Teams building video object detection, tracking, or action recognition models. Surveillance and security applications. Sports analytics. Manufacturing process monitoring. Any workflow where the training data is video rather than still images.
