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Trisha Lian, Kevin MacKenzie, Brian Wandell; Ray-tracing 3D Spectral Scenes Through Human Optics. Journal of Vision 2018;18(10):359. doi: 10.1167/18.10.359.
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Background. Display technology design benefits from a quantitative understanding of how parameters of novel displays impact the retinal image. Vision scientists have developed many precise computations and facts that characterize critical steps in vision, particularly at the first stages of light encoding. ISETBIO is an open-source implementation that aims to provide these computations. The initial implementation modeled image formation for distant or planar scenes. Here, we extend ISETBIO by using computer graphics and ray-tracing to model how spectral, three-dimensional scenes are transformed by human optics to the retinal irradiance. Methods. Given a synthetic 3D scene, we trace rays using PBRT (Physically Based Ray-Tracer) through an optical model of the human eye to obtain the spectral irradiance at the retina. The optical model specifies wavelength-dependent index of refraction and surface parameters; these are chosen to match the curvature, size, and asphericity of the cornea, lens, and retina. The methods can implement other eye models, including those with biconic surfaces. The simulation accounts for the chromatic dispersion of light in different ocular media, as well as the effects of accommodation and pupil size. Results. We compare the retinal irradiance generated from the simulation with experimental measurements from the literature. The sharpness of the computed retinal image matches statistical models. Further, the longitudinal chromatic aberration in our renderings closely matches experimental data. Conclusion. The ray tracing calculations enable us to understand the impact of different 3D display parameters on the retinal spectral irradiance. This ability may also prove useful for understanding the information available to the visual system to perform critical tasks, such as accommodation and vergence. The simulation tools are available in the ISETBIO Github repository.
Meeting abstract presented at VSS 2018
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