Capture White-Point Sensitivity in Frozen Vision Encoders: A Calibrated Audit on Human Faces

Frozen vision encoders are widely used as feature extractors for color-sensitive tasks such as dermatology, skin-tone auditing, and cosmetics, yet their color constancy under real capture changes has not been evaluated against physical measurements of the imaged surface. We audit twelve frozen encoders on 2,257 subjects photographed under a fully crossed $2\times 2$ design of capture white point and illuminance, each subject independently measured by a contact spectrophotometer. Changing white point at fixed illuminance moves embeddings by a large fraction of the distance between different people, along a direction shared across subjects; removing chroma eliminates this structure. Comparing encoder inputs and outputs, the perturbation enters as an almost shared translation and leaves as a subject-dependent residual more distributed than the difference between two people; a single-image gain ablation reproduces this with no pose or metering difference, while the white-point–illuminance interaction is already present at the encoder input at the level a separable multiplicative model predicts. The consequence is measurable in physical units: a skin-tone probe trained at one white point shifts the same person's predicted typology angle by several degrees under another and frequently changes the assigned skin-tone bin. We then compare corrections on one utility–invariance trade-off. Blind white balancing and a diagonal correction fitted to measured skin color do not reliably remove the sensitivity; projecting out a capture subspace estimated from unlabeled calibration captures recovers much of the cross-condition loss while preserving same-condition accuracy, and condition-mean differences estimate that subspace as well as paired displacements; pooling capture conditions when fitting the probe recovers the most.