typed op• Data kinds: video → video
• Call: fullseye.apply(img, "tb_running_gaussian_background", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
Sweeping knob a (0.1 / 0.5 / 0.9, the other knob at its default):
▸ tb_running_gaussian_background: knob a sweep (docs site)
Sweeping knob b (0.1 / 0.5 / 0.9, the other knob at its default):
▸ tb_running_gaussian_background: knob b sweep (docs site)
Stages (the ops that come before → this op, left to right):
▸ tb_running_gaussian_background: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_running_gaussian_background: other inputs (docs site)
Motion (GIF: frames / views / slices in turn. The still figure is the complete one; the GIF is supplementary):
Adaptive single-Gaussian background (the running mean) per frame → `(T, H, W) (video`).
> The detailed description below is the original text — the summary and the headings are translated.
画素ごとに平均 `mean と分散 var` を持つ単一ガウス背景(Wren の Pfinder)を
回し、各フレーム後の `mean` を返す。前景判定は
`(frame - mean)^2 > k^2 var。selective=True`(既定)では前景と判定した画素の
`mean / var` を更新しないので、ゆっくり動く物体が背景に溶けない。
更新式は `mean += α diff、var += α (diff^2 - var)、var` の下限は 1e-4。
• `video: (T, H, W) 配列か 2-D フレームの list。整数は最大値で [0, 1]`
に正規化、float はクリップ。NaN/Inf は `ValueError`。
• `alpha: [0, 1]` の学習率。既定 0.02(時定数およそ 50 枚)。
• `k: [0, 100]`。前景とみなす標準偏差の倍数。既定 2.5。
• `var_init: [1e-9, 1]。先頭フレームでの分散の初期値([0, 1]` 強度の 2 乗)。
小さすぎると 2 枚目から全画素が前景になり、`selective` で更新が止まる。
• `selective: 前景画素の更新を止めるか。False` なら全画素を常に更新。
• 返り値: `(T, H, W) float64。t = 0` は先頭フレームそのもの。
• 失敗: `ValueError`(形・dtype・各範囲)。
同じモデルの前景マスクは `running_gaussian_foreground`(同じ引数で対にすると
フレームごとに整合する)。
2-D 進化レジストリへ橋渡しした videostream の op `running_gaussian_background。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。a が alpha(既定 0.02)、b が k`(既定 2.5)を振る。
• 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.
The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
img_to_video 0.50 0.50 tb_running_gaussian_background 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op running_gaussian_background. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).
• video_streaming — py -3.11 examples/video_streaming.py
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
typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample
*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.