• a **tabletop light dome** — a small dome studded with controllable LEDs over an object on a stand — is the bench-scale version of the same idea: capture the object under each light direction (one LED at a time) to build a per-point reflectance / one-light-at-a-time (OLAT) stack for relighting, photometric stereo, and BRDF/normal capture. The miniature sibling of the room-scale [[#Light domes|light dome]] above.

• the dome idea taken *into the wild*: Murmann et al.'s **multi-illumination dataset** captures everyday indoor scenes under many controlled light directions (a flash bounced to a grid of directions, ~25 per scene over 1000 scenes), a no-dome stand-in for one-light-at-a-time capture out of the lab — training data for **single-image relighting**, illumination estimation, and learned reflectance separation. Same per-direction-capture principle as the dome, scaled to real rooms and a learning-sized corpus.

• mount a light on a **quadrotor** and let it *fly itself* into position: a feedback loop measures the subject's **rim light** (the bright contour that separates subject from background) and commands the drone to hold a target rim width/placement as the subject or photographer moves — the light source becomes an **autonomous, computationally-controlled actuator** rather than a fixed stand. Computational illumination where the optimized degree of freedom is the **light's position in space**.

• **confocal** illumination/imaging — co-focus the light source and the sensor on the same point (a pinhole rejecting everything off the focal point) so you isolate **single-scattering / direct** light and reject the multiply-scattered haze, the trick behind confocal microscopy and, computationally, behind direct/global separation and looking through scattering media (Ioannis Gkioulekas and collaborators). A coherent/structured-illumination cousin of the [[Separation of Direct and Global Illumination|direct/global separation]] separation above.