Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views

Abstract

Proposed and presented is a visual hull method and technique for reconstruction of realistic 3D shapes of snowflakes and other hydrometeors based on high-resolution photographs of particles in freefall from multiple views captured by a multi-angle snowflake camera (MASC), or another similar instrument. The visual hull of an object is the maximal domain that gives the same silhouettes as the object from a certain set of viewpoints. From the measured fall speed and the particle shape reconstruction, the particle density and dielectric constant are estimated. This is the first time accurate realistic shape reconstructions based on high-resolution photographs of real (measured) snowflakes are performed. The results are clearly much better than any similar data in the literature. They demonstrate – in experiments involved in real snow storm observations and those with simulated and fake 3D printed snowflakes – sufficient silhouette information from the five cameras of the expanded MASC system and excellent performance of the implemented mechanical calibration and software self-calibration of the system. In addition to enabling realistic "particle-by-particle" computations of polarimetric radar measurables for winter precipitation, the visual hull 3D shape reconstructions of hydrometeors can be used for microphysical characteristics analyses, hydrometeor classification, and improvement of radar-based estimations of liquid equivalent snow rates.