Download Reviewer # 5

This paper makes an important contribution to the modeling and animation of natural scenes, and is the
first to address important phenomena at such a large scale.
At the same time, all the reviewers expressed regrets that the paper seems incomplete: some important
phenomena are left out, when they would be pretty easy to model. And some, that would admittedly be
harder to implement, are completely ignored. In short, the paper, while it adds several contributions to the
state of Computer Graphics, also feels incomplete.
The paper was really borderline, and was considered for rejection several times. It is now conditionally
accepted, which means that you must implement all the changes suggested by the reviewers, and these
changes will have to be approved by the Primary.
A point where the reviewers are not sure: the voxel size is stated in the paper as 10 cm (0.1 m), but this
seems inconsistent with the grids shown in the figures, as well as with the overall aspect of the scenes:
the mountains and rocks seem much too smooth for a 10 cm voxel size. Could you please clarify? For
example, show the real grid superimposed with the mountain? At some point, the paper mentions very
large cell size, which somehow feels inconsistent with 10 cm voxel width.
Another point to clarify: what is your integration scheme? You mention 200 s time step, but for which
integration scheme? Euler? RK4? 200 s seems a very large time step for numerical integration, so could
you explain, and possibly compare the time step with the stiffness of your equations? Giving the value of
the stiffness would help assess whether 200 s is the proper time step.
Despite their severe marks, all reviewers would really like to see a follow-up on this paper that addresses
the harder issues:
- a more realistic terrain model, for example extracted from a Digital Terrain Model.
- more realistic phase changes: snow turns into water, not into air
- heat reflected onto world surfaces (radiosity)
- more realistic rendering (the BRDFs of snow and ice are not plausible)
- most importantly (but also hardest to add): the wind plays an essential role in winter scenery. It moves
snow, it changes its properties (transforms powder into packed snow, gives it a solid crust) and it can even
sublimate it (make it disappear into thin air).
Reviewer # 0
This paper presents a method for modeling (and, technically, animating) winter-based phenomenon in
natural scenes.
The phenomena being modeled are mostly water freezing and thawing in lakes and ponds, and snow
falling (and melting). The paper models the exchanges of heat inside the scene, physically. The results
are impressive with respect to the natural phenomena being modeled, less so for visual realism.
Originality, Novelty 8
Although modeling natural scenes is an ongoing research theme, a physical modeling of natural
phenomena occurring in winter is less frequent. The approach used in this paper produces interesting and
realistic results.
Clarity of Presentation 4
This is clearly the single point where the authors could really improve their paper.
The paper has 11 sections. Which is another way of saying that there is no high-level organisation, no
hierarchy in the presentation? I would suggest grouping sections together, presenting thing in order of
importance, hierarchically, in order to make things easier for the reader. Some parts of the paper are
redundant, like sentences describing equations.
For some of the functions you introduce, a simple curve to show how they evolve would also help the
reader (phi_sun, for example).
There seems to be an inconsistency just before the title of section 5.1: ''(...) Thus, only the direct radiative
transfers are taken into account. All the other heat transfers are taken into account (...)''. So, are they
taken into account or not?
I'm not sure about ''deepness'', since ''depth'' seems to have the same meaning, and is in my dictionary.
Minor issues: ''the thermal cut corresponding *to* the three images ...'', ''It is frozen during most of the
year'' (or ''most of the time during the year'').
Technical Soundness 6
I am of mixed feelings here. On one hand, this is one of the first papers to model heat exchanges in
natural scenes with great physical accuracy, including latent heat for phase changes. I appreciate that.
On the other hand, I am disappointed with some of the assumptions made by the authors. They did a lot of
work for physical accuracy, and in the end they add several strong approximations that disrupt this
physical accuracy. Having gone so far for physical accuracy, it seems strange to leave key elements out.
Namely: why separate between snow and water/ice? When snow melts, it should convert into water, and
this water should be absorbed by the ground (or lake), changing its characteristics (from dry ground to wet
ground). I don't see this as really increasing the complexity of the algorithm. Having snow melting into air
is strange, reduces the realism and does not really simplify the implementation.
Also: why treat water and snow as identical in terms of precipitation?
It is well know that a certain amount of rain transforms into a much larger depth of snow. 1 cm of rain
becomes 10 cm of snow with the right temperature. Yet this effect is completely neglected in the paper.
Again, I can see what you lose by doing this (in terms of realism) and I don't see what you gain (in terms
of simplicity).
Third: while I agree that radiosity in general is very complex, especially for lighting simulations, I do not
think that using radiosity *in this specific settings* would be so difficult:
- the scene is already discretized,
- it contains a small number of patches (according to your measures, it's a 200*200 grid, approximately).
- the scene is mostly a height field, making visibility between patches easy to compute.
- we do not need accuracy in shadow boundaries (there's no need to do discontinuity meshing). A
pixelized shadow works fine for heat transfers (less so for illumination).
In short, given your implementation, it should be straightforward to add the reflection of heat on the
surfaces of the scene, thus giving the first bounce of heat, instead of just direct heat. I believe this would
really increase the realism of the scene, without making the algorithm much more complex.
This phenomenon is visible in the mountains: the sun is reflected by the southern-facing slope of the
valley, melting snow on the bottom of the northern-facing slope (for a valley in the northern hemisphere,
the opposite for a valley in the southern hemisphere, of course).
Importance, Utility 7
Again, I am of mixed feelings here.
I agree that this paper is an important contribution for accurate representation of natural scenes, but I
believe in order for it to really have an impact, it increase its physical accuracy.
I'm also unsure about the choice by the authors to define the rock surface as a convolution surface. Is that
really necessary? Could their work be extended to any kind of surfaces (and they just used convolution
because they had it around?)
Could I (the reader) use this technique with another Digital Terrain Model? By the way, could you? It
would greatly increase the realism of the scenes you're generating, and I don't see why not.
Completeness of References 8
The references seem complete, but I'm not the expert here.
Confidence 3 - Overall Recommendation 8
This paper represents a significative contribution to the field of realistic modeling of natural scenes. Thus, I
would really like to see it published, preferably with the issues I raised in ''Technical Soundness''
addressed, but I won't make it a strong issue (some of them are better left for future work).
Whether it is published as it is, in its current and imperfect state, or later, in a better state, I will definitely
enjoy reading this paper and giving it to my students.
Reviewer # 2
The paper describes a system for generating realistic winter scenes. The approach employs heat transfer
models and considers materials such as rock, water, ice and snow. Phase changes are also incorporated.
Results with static scenes are presented.
Originality, Novelty 5
The paper mainly focuses on the governing equations and on appropriate parameter settings within these
equations. The discretization of the equations, rendering or mesh generation are only briefly explained.
While the approach seems to be dynamic, all presented results are static and dynamic effects cannot be
assessed. So, the contribution is only marginal and I am also wondering if the focus is appropriate for
EUROGRAPHICS.
Clarity of Presentation 5
The presentation is clear and detailed. However, the presentation is rather narrow and only focused on the
governing equations.
Technical Soundness 5
The technical soundness is difficult to assess as relevant components of the framework are not sufficiently
described.
Importance, Utility 5
Again, this is difficult to judge. The system seems to provide useful results, but from my perspective, it
would be nice to also demonstrate dynamic effects. Further, benefits and limitations of the framework are
not thoroughly discussed, e. g. the handling of melting ice on tilted surfaces.
Completeness of References 7
Confidence 4 - Overall Recommendation 5
I would mainly be concerned about the focus of the paper and the utility of the results. The paper mainly
describes known governing equations, but it is difficult to identify a contribution in terms of simulation or
visualization. If the paper is considered as a systems paper, then the discussion of the utility and the
limitations is not sufficient. In terms of the results, dynamic scenarios would be of interest, as the
framework simulates the dynamics of the winter scenario.
Reviewer # 3
This paper presents a physically based method to generate realistic winter sceneries. This method takes
as input a voxel based terrain model and a user controlled weather model defining air temperatures, rain
and snow fall, cloud cover, etc. It produces as output the temperature of each terrain voxel at each time
step, as well as the quantity of snow, ice and water in each voxel. The method uses a numerical
simulation scheme to simulate the conductive, convective and radiative heat transfers between voxels, as
well as the phase changes between snow, ice and water. Finally, the voxel data is converted to four
textured meshes with procedural details for rendering the terrain, snow, ice and water layers.
The main contribution of the paper is a clear and self-contained summary of the physical processes and
constants involved in the evolution of snow, ice, and water in landscapes.
Originality, Novelty 6
The most original aspect is the idea to simulate the evolution of snow, ice and water with time in a
landscape (most previous methods simulate only the snow fall. They do not simulate its evolution with
time). The use of a voxel grid to simulate the physical processes, the convolution surfaces to generate the
meshes from the voxels, and the physical equations are not new.
Clarity of Presentation 7
The presentation is clear, except in section 9.2. I'm not sure to understand correctly how the water and ice
meshes are generated.
Technical Soundness 5
The overall method is sound but some points are unclear while others are not presented but are needed to
implement the algorithm.
- it is not clear whether you simulate rain or not. Rain is discussed in section 4, but you do not discuss how
you simulate rain flowing on the ground, and you do not have water-air voxels, so I presume rain is in fact
not simulated. In this case you should say that in section 4.
- you introduce a percentage of solid material for phase changes, and a percentage of each material for
two-material voxels (section 3). Are these percentages the same (ie. do you store one or two percentages
per voxel)? For a ice-water voxel I would say yes. But for a snow-air voxel I would say no (the percentage
of snow vs air cannot represent the melting of snow, ie. the percentage of snow vs water). Since you
convert melted snow into air I think the handling of snow melting is a special case that should be precisely
explained (you must also specify the initial temperature of new snow voxels). I presume that the
percentage of snow vs water is r = Q_hole / L_f rho V_s, where V_s is the volume of snow and water,
equal to V times the percentage of snow+water vs air.
- in section 5 you use both voxel and surface temperatures. The use of surface temperatures is
ambiguous since only voxel temperatures are simulated. For instance for the radiative heat transfer
between rock and water, do you compute T_interface as 0.5*(T_rock+T_water)? or do you compute in fact
phi_interface using T_rock^4-T_water^4?
- it is not clear how you handle two-material voxels during heat transfer simulation. Two two-material
voxels in contact can give three different kinds of interfaces, whose areas depend on the percentage of
material in each voxel. I presume you compute the heat flow between the two voxels as the sum of the
heat flows for each interface, using the areas of these interfaces. But it is stated nowhere. It is also not
clear how you compute the variation of temperature for a two-material voxel (for a water-ice voxel there is
no variation since there is a phase change; but for a snow-air voxel, how do you generalize the dQ=rho
C_p V dT relation? dQ=(sigma rho_i C_p,i V_i)dT? You must explain that somewhere).
- in section 8, you do not explain how you average the temperature of water above 277K. Do you compute
the average using neighbor voxels only, or using all the connected water voxels above 277K? In the first
case the result may depend on the time step and the voxel size, which is not correct.
- you do not discuss if you need to rearrange voxels or not. For instance if ice forms in a water voxel below
the surface, do you need to move this ice to the upper voxel if it is not completely frozen? Or is this case
impossible?
- the snow mesh is obtained by elevating the vertices of the ''terrain mesh''. I presume you mean
terrain+ice mesh, since snow can accumulate on frozen lakes. You should clarify this. Also why don't you
use a convolution surface for snow (like for terrain, water and ice)? Why do I have the impression in
figures that the snow layer is floating above the terrain (shadows around snow areas)? The generation of
the water and ice meshes is not clear. In fact the generation of the water mesh is not explained (how do
you use f_water? it seems you have no guaranty that f_water=0 is a horizontal and flat surface, as it
should be)
Importance, Utility 7
Simulating snow fall, accumulation and evolution is an important topic for Computer Graphics, as shown
by the previous papers on this topic.
Completeness of References 7
Implementation 5
The overall algorithm is simple to implement, but some important aspects of the model would need to be
guessed since they are not presented in the paper: the boundary conditions on the vertical boundaries of
the domain, the precise method used to simulate snow fall and stabilization (if it is an existing method, a
reference to it would suffice), the initial temperature of new snow voxels after snow fall simulation, the
equations for heat transfers and temperature variations for two-material voxels, the averaging method
used to simulate natural convection in water, a clear description of the method used to generate the ice
and water meshes.
Confidence 3 - Overall Recommendation 5
Simulating the evolution of snow, ice and water according to the weather in landscapes is an original idea.
The main contribution of the paper is a clear summary of the physical processes and constants involved in
these phenomena. However many aspects of the algorithm are unclear or missing (boundary conditions at
vertical boundaries, handling of rain, of two-material voxels, or interface temperatures, etc). I think these
aspects could be explained in a few sentences, and would make the paper acceptable.
Required changes: provide an explanation for the points discussed in ''technical soundness''
Minor changes: - abstract: ''snow fall and its stabilization''. What do you mean by ''stabilization''? Is it part
of the snow fall simulation step (step 2 in Fig. 4)? ''snow melting into water''. Remove ''into water'' since
you convert melted snow into air (section 7).
- overview: give the reference of the method you use to simulate snow fall and accumulation. Do you take
wind and terrain slope into account in this step?
- section 7: energy injected to the material *increases* its temperature. From liquid to solid energy is
removed from the material. For Q_hole to be positive, if defined as an ''absorbed energy'', I think you
should define it for the solid to liquid transition.
- section 10: I would like to have the memory requirements of the simulations
typos:- section 3: ''from the the''
- section 5.5: ''solar radiance'' -> ''solar irradiance''
- section 7: ''his temperature'' -> ''its temperature''
- section 9: ''thinkness'' -> ''thickness''
- section 10: ''whereas the second one which is warmer'' -> ''whereas the second one is warmer'', ''height
voxels'' -> ''eight voxels''
Reviewer # 5
This paper presents the first graphical method of simulating snow and ice formation in large winter scenes
by taking into account the salient forms of heat transfer.
Originality, Novelty 8
Clarity of Presentation 6
The clarity is fine for the most part, but there are a few issues that could be addressed. Gendered
pronouns incorrectly appear in several places, e.g. section 7, first paragraph, ''decrease his temperature
any more''. Also, section 9.2, ''a set of connex water, ice'' -- what is a connex? Connected?
Technical Soundness 7
Importance, Utility 7
Completeness of References 8
Implementation by Graduate Student 6
The system is obviously a large and complex one, even before the Arches framework is introduced for
rendering. It would take quite a dedicated graduate student to reproduce the results, but it should be
possible.
Confidence 5 - Overall Recommendation 8
Full disclosure: I reviewed an earlier version of this paper at a different venue. I thought that it was
excellent then, and was very disappointed when it was not accepted. I am very happy to see that the
authors have continued to pursue this work and have produced an even higher quality manuscript. The
overall novelty is very clear, as no previous work that I am aware of has attempted to address scenes of
this scale. The types of heat transfer modeled have been chosen judiciously, and the results are
convincing. I have several comments below, but overall this paper is very good.
1. My primary concern is that the integration method is still unclear to me. From the second to last
paragraph in Section 3: ''To solve the inhomogeneous heat equation, we compute the different heat flows
between the elements in the scene, using the corresponding material coefficients.'' This only describes
derivative computation, not how the final solve uses these derivatives to integrate forward in time. It is fine
if just forward Euler is employed, and if that is the case, I am happy to see that the method is stable
enough that a simple integration method suffices. However, I would still like to see the integration method
spelled out explicitly.
2. There are many heat flow terms described in section 5 (I count 8) and a large number of corresponding
parameters that account for a wide variety of heat transfers. Some are surely more dominant than others,
so I would like to see some discussion of which parameters were found to be the most influential when
generating the results. For example, in Figure 9, the ''Solar energy'' transfer term is clearly most
responsible for the overall visual appearance.
3. From the last paragraph of section 7: '' One of the limitation [sic] of our method is that when snow melts,
it is converted to air and not water''. This implies sublimation, which only occurs below a certain
temperature. Does this cause artifact for warmer scenes?
4. Finally, the last paragraph in the introductory subsection of Section 5 mentions that radiative transfer is
considered negligible. This is reasonable for naturalistic environments, but it is easy to imagine a
manmade environment where it would not be -- an urban environment with many windows casting
caustics for example. Could this method be extended to such environments?
Reviewer # 4
This paper describes a finite volume approach to the thermal modeling of snowpack dynamics. A coarse
voxel grid is used for finite volume computation of the thermal changes. This is coupled with a procedural
instantiation method for surface and texture details of ice and snow from the computed thermal model.
The phase transitions allowed are from water to ice and from snow to air. There is no snow to water phase
transition.
The simulation runs with day/night periods affecting the radiative transfer from the sun. Lake water is
simulated as either convective mixing (averaging in the simulation) or stratified.
Rendering of the snow and ice is beyond the scope of the paper but the authors use a simple instantiation
method for representing snow and water is textured representing liquid or solid (water or ice).
The main contribution of this paper is a simplified simulation of the thermal coupling of earth, snow, water
and air. The coarse voxelization limits the physical reality of the results. It is not clear whether there are
limitations due to the thermal simplifications taken: such as snow sublimating rather than melting, thermal
mixing of the water and shading effects of the scene.
Originality, Novelty 5
This paper takes standard finite volume simulation for thermal transfer and applies it to the problem of
modeling winter scenes. The model used does not appear to be state of the art with respect to snow-pack
modeling where the main characteristics of the snowpack: snow-water equivalent, density, depth and
albedo need to be considered for snow-pack modeling (Recent advances in the modeling of hydrologic
systems By David S. Bowles, P. Enda O'Connell, Chapt 6, a physically based snow cover model).
Due to the simplifications, the results do not appear very realistic though the thermal coupled model likely
is correct with the assumptions made.
Clarity of Presentation 7
The paper is easy to read, although, the physical assumptions should be grouped and made more explicit.
Technical Soundness 4
Due to the assumptions made, the results are less than stunning. In the video clip, snow appears to flicker
which must mean state-change instability. However, no mention of this was made in the paper. While the
authors are clear that the goal is modeling and not rendering, the rendered results do not look very nice.
The instantiation method is not a strong contribution to the paper.
How does this method compare to standard methods for modeling snowpack. There are many simulation
packages for modeling snowpack but the reader is left to ponder how the proposed method compares with
others.
With the voxelized method, how is vegetation modeled? This seems to be lacking the simulation.
Importance, Utility 8
A good model for physical phenomena is always important for modeling outdoor scenes.
Completeness of References 6
The authors should compare and reference other snow-pack simulation systems.
Confidence 3 -Overall Recommendation 4
Due to the visual results, this paper is not quite up to Eurographics standards. The results do not convince
the reader that this simulation method is accurate.
The author’s contributions are stated as:
1. A model for air/dew-point temps, precipitation, day/night cycles and cloud cover 2. Finite volume
thermal simulation. 3 Simple phase changes 4. Instantiation for rendering
Of these, the authors succeeded in 1 and 2. The simple phase changes are neither physically correct nor
realistic and the rendering quality is not really a contribution.
My rating is based on the flaws in the modeling as detailed below.
In general, the results are not compelling. For example, in the Eychauda comparison, the snow-pack in
the shadow of the photograph is incorrectly modeled. Is this due to some simplifying assumptions or due
to the lack of resolution in the model.
In the paper, you state that a coarse grid is used due to memory constraints yet most physics simulations
would use AMR to avoid this problem.
The state changes limited to air-snow and ice-water is a big limitation. This does not capture the physics
of the underlying process. Perhaps this is why the results do not appear correct.
The reference to PTS99 does not indicate the simulation they used for snowpack. Their method was
surface based rather than volume based but the results are much more impressive. Their results appear
realistic whereas the results in this submission appear less so.
This reviewer is not convinced the lake model of thermal clines in winter with complete mixing in
spring/autumn is realistic. Typically, there is a layer where the mixing occurs but rarely does it penetrate
this layer.
While the rendering of snow and ice is beyond the scope of this paper, the textured mesh representation
presented is poorly done. This reviewer accepts that this is not the main goal of the paper but a better job
should be done to present convincing results. That said, the modeling (where the snow appears on the
mountains, does not appear to be correct. Comparing with the photograph demonstrates significant visual
differences with where the snow appears but just in the snow appearance. That is, the snow is not
appropriate placed (modeled) with this simulation.
The authors neglect a vast amount of theory and practice for snowpack modeling. A google search turns
up many physics papers and books addressing this topic although not from a computer graphics stand
point. Typically computer graphics simulations point out the differences in assumptions and the limitation
these impose. The authors do not provide this information.
Typos: page 3, 3rd paragraph, left column: ''...allows knowing the exact...'' would be better worded as:
''...allows knowledge of the exact...''
Page 5, column 2, 5th paragraph: ''... by setting his emissivity...'' should be: ''... by setting this emissivity...''