tb_exponential_foreground — 2D `typed` op

• Data kinds: video → video

• Call: fullseye.apply(img, "tb_exponential_foreground", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Foreground masks `|frame − exponential background| > threshold → 0/1 (T, H, W) (video`).

Typed bridge of the videostream op `exponential_foreground into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives alpha (default 0.05) and b drives threshold` (default 0.1).

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept `video` as input)

identity · tb_temporal_bandpass · tb_temporal_band_power · tb_temporal_median_window · tb_moving_average_window · tb_background_subtraction_window · tb_frame_difference_causal · tb_exponential_background

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_exponential_foreground — 2D typed op