Camera Identification Distance Calculator

Computes max identification distance from FoV + sensor pixels + min pixel footprint. Full dome scan time is max(mechanical, camera) where camera time assumes 1 frame per tile. Adds a motion blur limiter (default worst-case lateral motion) using a blur budget as a fraction of the object footprint.
Ready

Inputs

Preset: Default
deg
deg
Top-down visualization uses FoV width only.
deg
deg
deg/s
deg/s
%
fps
m/s
Scan time uses a row-scan pattern: pan across full azimuth for each elevation row, then tilt by one step.
px
mm
px
mm
Sensor mm is used to estimate focal length and f-number. Distance math uses FoV (deg) + sensor px.
lux
ISO
0-1
ratio
Exposure estimate is approximate. Real results depend strongly on optics transmission, QE/efficiency, and scene.
0-1
0-1
% of footprint
Blur budget is applied to the object footprint: allowed blur = blurFrac * min(objPxW, objPxH) at distance D. Default assumes worst-case lateral motion from object only.
m
m
Assumes object face is roughly perpendicular to the camera axis.
px
px
Interpret as the minimum pixel footprint to identify the object (model or human).

Results + visualization

-
FoV wedge (top-down) Width dist (dashed) Height dist (dotted) Final dist (solid) Blur dist (dash-dot) Object arrow + max travel Side profile (FoV height)
Scale: -
Max identification distance (final)
- m
-
Dominant distance constraint
-
-
Lensing (from sensor mm + FoV)
- mm
-
Pixels per degree
- px/deg
-
Full dome scan time
- s
-
Dominant scan constraint
-
-
Required f-number (1 frame per tile)
- f/
-
Dominant exposure constraint
-
-
Max distance traveled before full scan
- m
-
Feasibility
-
-
Sensitivity (what-if)
Recomputes key outputs under simple multipliers to show what actually moves the needle.
Baseline
-
Scenario
-
Metric Value Notes