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What is Motion Estimation?

Motion estimation determines how image regions move between video frames and represents that movement with vectors or other models. It supplies motion information for prediction, analysis, or image alignment.

How Motion Estimation works

Motion estimation searches for a mapping between regions in related frames, producing displacement candidates and a measure of prediction error. Video encoders use these candidates when deciding whether inter-frame coding costs less than spatial coding. Other systems interpret motion for stabilization, tracking, interpolation, or alignment, where the desired model may be dense, global, or feature-based. Search range, precision, and metric determine the tradeoff between computation and accuracy.

Key facts

  1. Block-matching encoders commonly compare candidates with measures such as sum of absolute differences, then include vector signaling cost when choosing the best coded mode.
  2. A motion vector is a prediction parameter, not necessarily the physical trajectory of an object. Occlusion, texture repetition, camera movement, and rate optimization can change it.
  3. Fractional-pixel vectors require interpolated reference samples. They can improve prediction around slow or diagonal motion but increase both search work and decoder filtering.

When Motion Estimation matters

Use motion estimation for compression, stabilization, frame interpolation, tracking, or motion analysis. A wider or more precise search may improve accuracy but raises latency and computational cost.

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