Capturing Rich Details of Human Eyes

Capturing rich details of human eyes is essential for realistic digital humans, yet remains challenging due to the eye's complex optical structure. The sclera, cornea, and iris exhibit distinct appearance properties, and their geometry and appearance are tightly coupled through reflection and refraction in image observations. We present a human eye capture and reconstruction system based on multi-source optical measurements, which are tailored to different eye components to capture detail-rich observations at multiple scales and provide direct constraints for staged, decoupled reconstruction. For the sclera, multi-view and multi-gaze imaging recovers subject-specific exterior geometry and establishes an eye-centric frame. For the cornea, specular highlights and dense Placido-based topographic cues estimate the anterior surface before it is used as the refractive interface for iris reconstruction. For the iris, refraction-aware photometric reconstruction recovers albedo, normals, and fine-scale displacement under limited viewing angles. Experiments demonstrate detailed reconstruction of scleral shape, corneal topography, and iris micro-geometry across diverse subjects. The reconstructed assets further expose physiology-supported ocular details, including scleral asymmetry, non-axisymmetric corneal shape, iris relief, and pupil-center motion, providing evidence for reconstruction fidelity and useful annotations for downstream rendering, tracking, and data generation. We will release a consented 20-eye reconstructed ocular asset dataset containing component models and textures for all eye components.