Name: Dyn Object Masks
Author: benchflow-ai

When to use

Detect moving objects in scenes with camera motion; produce sparse masks aligned to sampled frames.

Workflow

Global alignment: warp previous gray frame to current using estimated affine/homography.
Valid region: also warp an all-ones mask to get valid pixels, avoiding border fill.
Difference + adaptive threshold: diff = abs(curr - warp_prev); on diff[valid] compute median + 3×MAD; use a reasonable minimum threshold to avoid triggering on noise.
Morphology + area filter: open then close; keep connected components above a minimum area (tune as fraction of image area or a fixed pixel threshold).
CSR encoding: for final bool mask
- rows, cols = nonzero(mask)
- indices = cols.astype(int32); data = ones(nnz, uint8)
- counts = bincount(rows, minlength=H);

Detect moving objects in scenes with camera motion; produce sparse masks aligned to sampled frames.

Global alignment: warp previous gray frame to current using estimated affine/homography.
Valid region: also warp an all-ones mask to get valid pixels, avoiding border fill.
Difference + adaptive threshold: diff = abs(curr - warp_prev); on diff[valid] compute median + 3×MAD; use a reasonable minimum threshold to avoid triggering on noise.
Morphology + area filter: open then close; keep connected components above a minimum area (tune as fraction of image area or a fixed pixel threshold).
CSR encoding: for final bool mask
- rows, cols = nonzero(mask)
- indices = cols.astype(int32); data = ones(nnz, uint8)
- counts = bincount(rows, minlength=H);