Table 4 Various presented methods (2012–2019) compared for their modeling, rendering and animation times (\(T_{m}\), \(T_{r}\) and \(T_{a}\), respectively)
From: A survey of modeling, rendering and animation of clouds in computer graphics
Method | Model size (g/p) | \(T_{m}\) | \(T_r\) | \(T_a\) | Feature |
|---|---|---|---|---|---|
[12]-2012 | \(200\times 200\times 200\)/– | – | 30 s | – | Image-based (GPU) |
[107]-2014 | \(100\times 100\times 200\)/80 K | 5 min | – | – | Image-based (CPU) |
[109]-2014 | –/10 K | – | 36 ms | – | Precomputed lighting (GPU) |
[2]-2015 | –/840 K | – | – | 1219 ms | Position-based fluids (GPU) |
[28]-2016 | –/49K | – | 1173 ms | – | Lennard–James potential (CPU) |
[34]-2017 | –/82 | – | 42 ms/fr | 4.3 ms/fr | Macro-physics (CPU), micro-rendering (GPU) |
[24]-2017 | –/250K | – | – | 44 ms/fr | SkewT/LogP diagram (CPU) |
[49]-2017 | \(1200\times 1200\times 1200\)/– | – | 9 min | – | Deep scattering, RPNN (GPU) |
[99]-2018 | – | – | 10 s/fr | 30 min | Key-frame interpolation, morphing (GPU) |
[32]-2019 | –/12 | – | 3.3 ms/fr | 1.6 ms/fr | Cloud map, macro-physics |