Visual Hull Method for Realistic 3D Particle Shape Reconstruction Based on High-Resolution Photographs of Snowflakes in Free Fall from Multiple Views
Abstract
A visual hull method for reconstruction of realistic 3D shapes of snowflakes and other hydrometeors based on high-resolution photographs of particles in free fall from multiple views captured by a multiangle snowflake camera (MASC), or another similar instrument, is proposed and presented. 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 3D shape reconstructions based on multiple 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 snowstorm 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.
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