Frame interpolation
Frame interpolation is a technique that creates new in-between video frames by estimating motion between existing frames. It can raise a video's frame rate, for example from 30 to 60 frames per second, or produce smooth slow motion. Modern approaches use motion estimation or AI models to predict what the missing frames should look like.
Why it matters
Frame interpolation lets businesses reuse footage at new frame rates and create slow motion without special cameras. It helps when content must match different broadcast standards or when smoother motion improves the viewing experience. Poor interpolation, though, creates visible warping and artifacts that make video look cheap.
How it works
- The system compares two neighboring frames to estimate how each part of the picture moved.
- It predicts where each object would be at a point in between the two frames.
- It builds a new frame from that prediction, filling gaps where objects were hidden.
- It inserts the new frames to raise the frame rate or stretch time for slow motion.
Is frame interpolation good or bad?
Frame interpolation is good for slow motion, sports replays and frame rate conversion, but many viewers dislike it on films. On TVs it causes the so-called soap opera effect, where movies look overly smooth, like video. It can also create warping around fast-moving objects. Its value depends on the content and the quality of the method.
Can AI make a 30fps video 60fps?
Yes, AI frame interpolation can turn 30 fps video into 60 fps by generating one new frame between each pair of real frames. Modern AI models handle motion better than older methods, with fewer ghosting effects. Results are weaker on very fast motion, scene cuts and fine details such as hair or text.
Where it's used
OTT services and sports broadcasters use frame interpolation to convert content between frame rates or produce smooth slow motion from ordinary footage.
