Assume I have a model that is simply a cube. (It is more complicated than a cube, but for the purposes of this discussion, we will simplify.)
So when I am in Sketchup, the cube is Xmm by Xmm by Xmm, where X is an integer. I then export the a Collada file and subsequently load that into threejs.
Now if I look at the geometry bounding box, the values are floats, not integers.
So now assume I am putting cubes next to each other with a small space in between say 1 pixel. Because screens can't draw half pixels, sometimes I see one pixel and sometimes I see two, which causes a lack of uniformity.
I think I can resolve this satisfactorily if I can somehow get the imported model to have integer dimensions. I have full access to all parts of the model starting with Sketchup, so any point in the process is fair game.
Is it possible?
Thanks.
Clarification: My app will have two views. The view that this is concerned with is using an OrthographicCamera that is looking straight down on the pieces, so this is really a 2D view. For purposes of this question, after importing the model, it should look like a grid of squares with uniform spacing in between.
UPDATE: I would ask that you please not respond unless you can provide an actual answer. If I need help finding a way to accomplish something, I will post a new question. For this question, I am only interested in knowing if it is possible to align an imported Collada model to full pixels and if so how. At this point, this is mostly to serve my curiosity and increase my knowledge of what is and isn't possible. Thank you community for your kind help.
Now you have to learn this thing about 3D programming: numbers don't mean anything :)
In the real world 1mm, 2.13cm and 100Kg specify something that can be measured and reproduced. But for a drawing library, those numbers don't mean anything.
In a drawing library, 3D points are always represented with 3 float values.You submit your points to the library, it transforms them in 2D points (they must be viewed on a 2D surface), and finally these 2D points are passed to a rasterizer which translates floating point values into integer values (the screen has a resolution of NxM pixels, both N and M being integers) and colors the actual pixels.
Your problem simply is not a problem. A cube of 1mm really means nothing, because if you are designing an astronomic application, that object will never be seen, but if it's a microscopic one, it will even be way larger than the screen. What matters are the coordinates of the point, and the scale of the overall application.
Now back to your cubes, don't try to insert 1px in between two adjacent ones. Your cubes are defined in terms of mm, so try to choose the distance in mm appropriate to your world, and let the rasterizer do its job and translate them to pixels.
I have been informed by two co-workers that I tracked down that this is indeed impossible using normal means.
Related
Let's say I have a static object and a movable object which can be moved and rotated, what is the best way to very quickly calculate the difference of those two meshes?
Precision here is not so important, speed is though, since I have to use it in the update phase of the main loop.
Maybe, given the strict time limit, modifying the static object's vertices and triangles directly is to be preferred. Should voxels be preferred here instead?
EDIT: The use case is an interactive viewer of a wood panel (parallelepiped) and a milling tool (a revolved contour, some like these).
The milling tool can be rotated and can work oriented at varying degrees (5 axes).
EDIT 2: The milling tool may not pierce the wood.
EDIT 3: The panel can be as large as 6000x2000mm and the milling tool can be as little as 3x3mm.
If you need the best possible performance then the generic CSG approach may be too slow for you (but still depending on meshes and target hardware).
You may try to find some specialized algorithm, coded for your specific meshes. Let's say you have two cubes - one is a 'wall' and second is a 'window' - then it's much easier/faster to compute resulting mesh with your custom code, than full CSG. Unfortunately you don't say anything about your meshes.
You may also try to make it a 2D problem, use some simplified meshes to compute the result that will 'look like expected'.
If the movement of your meshes is somehow limited you may be able to precompute full or partial results for different mesh combinations to use at runtime.
You may use some space partitioning like BSP or Octrees to divide your meshes during precomputing stage. This way you could split one big problem into many smaller ones that may be faster to compute or at least to make the solution multi-threaded.
You've said about voxels - if you're fine with their look and limits you may voxelize both meshes and just read and mix two voxel values, instead of one. Then you would triangulate it using algorithm like Marching Cubes.
Those are all just some general ideas but we'll need better info to help you more.
EDIT:
With your description it looks like you're modeling some bas-relief, so you may use Relief Mapping to fake this effect. It's based on a height map stored as a texture, so you'd need to just update few pixels of the texture and render a plane. It should be quite fast compared to other approaches, the downside is that it's based on height map, so you can't get shapes that Tee Slot or Dovetail cutter would create.
If you want the real geometry then I'd start from a simple plane as your panel (don't need full 3D yet, just a front surface) and divide it with a 2D grid. The grid element should be slightly bigger than the drill size and every element is a separate mesh. In the frame update you'd cut one, or at most 4 elements that are touched with a drill. Thanks to this grid all your cutting operations will be run with very simple mesh so they may work with your intended speed. You can also cut all current elements in separate threads. After the cutting is done you'll upload to the GPU only currently modified elements so you may end up with quite complex mesh but small modifications per frame.
We need to convert some specific stream 2D video to 3D video with some symbologies on it. To make an example:
<iframe width="640" height="360" src="https://www.youtube.com/embed/-YKYjigYgok" frameborder="0" allowfullscreen></iframe>
edit: I added the video link here due to some errors in HTML insertion.
this is something similar to our project. As you can see, heights are indexed as colors, some shades, shadows are also are seen. the question is, can we convert those mountains and other shapes into 3D in a simple way? I ve seen many 2D-3D converters out in the market but they are undeterministic. We want to make our niche software for this and don't know where to start. We can utilize colors and shadows(for height and light direction) and also we have the altitude of the plane. Once we handle the mountains and other contents, putting 3D symbology is not an issue for us.
What I seek here is just some direction to get this done in a fastest way. Regards.
I think what you're looking for is called heightmap. You start from a 2d matrix with the height values in every cell and generate a 3D terrain based on the matrix.
The naive way to do it is to assign a vertex to each point in the matrix and then link them together with simple triangles.
As you can imagine is your map is large this will mean a lot of triangles. There are techniques that try to compress flat spaces or things that are very far away so that you spend the triangles on areas where they add more details. See for example quad-trees. This is also why some renderings seem non-deterministic since the algorithm is going to change the geometry on far away things in a way that it becomes visible. This can be solved by tunning the algorithms and put a larger weight on how visible the change is. A cheap-ish way of doing it is to measure the volume difference between the different levels of details, but only works decently when you don't have sharp spikes or pits in you map.
I assume assigning colors to the heights is not a problem here.
I'm experimenting some issues when work with real worlds.
The center of my camera is 280000, 45787254 (for example).
The extension of my world is about 500 x 500 (not too big)
I'm using data based in metric units (meters).
I have created a tile map structure build with simple planes.
I see little gaps between the plane borders and this planes are built to be contiguous (that is xmin of the adjacent plane is equal to xmax of previous).
In the past I have issues related with ray cast.
Matrix projection with this big units have low precision.
Change near value to number great than 10 can be the fix. However, using this value means bad visualization (you can't place the cam much near of the scene, it disappears).
I talked with the guy who develops potree and he said me is had to move the lidar worlds to 0,0 to work properly.
So... the final solution is to work in 0,0 worlds, isn't it ?
Or is there any trick we can do at matrix calculations?
I'd like to know three.js developers.
Floating point math is best at ranges close to zero, you just end up compounding errors as you move far away. You can always do as much math as possible near the origin and then translate the result to wherever you need, that will help with some of it, but if you can, work in local coordinates.
Potree probably gets odd ripple-looking aliasing effects when too far from the origin, no?
Many certain resources about raytracing tells about:
"shoot rays, find the first obstacle to cut it"
"shoot secondary rays..."
"or, do it reverse and approximate/interpolate"
I didnt see any algortihm that uses a diffusion algorithm. Lets assume a point-light is a point that has more density than other cells(all space is divided into cells), every step/iteration of lighting/tracing makes that source point to diffuse into neighbours using a velocity field and than their neighbours and continues like that. After some satisfactory iterations(such as 30-40 iterations), the density info of each cell is used for enlightment of objects in that cell.
Point light and velocity field:
But it has to be a like 1000x1000x1000 size and this would take too much time and memory to compute. Maybe just computing 10x10x10 and when finding an obstacle, partitioning that area to 100x100x100(in a dynamic kd-tree fashion) can help generating lighting/shadows for acceptable resolution? Especially for vertex-based illumination rather than triangle.
Has anyone tried this approach?
Note: Velocity field is here to make light diffuse to outwards mostly(not %100 but %99 to have some global illumination). Finite-element-method can make this embarassingly-parallel.
Edit: any object that is hit by a positive-density will be an obstacle to generate a new velocity field around the surface of it. So light cannot go through that object but can be mirrored to another direction.(if it is a lens object than light diffuse harder through it) So the reflection of light can affect other objects with a higher iteration limit
Same kd-tree can be used in object-collision algorithms :)
Just to take as a grain of salt: a neural-network can be trained for advection&diffusion in a 30x30x30 grid and that can be used in a "gpu(opencl/cuda)-->neural-network ---> finite element method --->shadows" way.
There's a couple problems with this as it stands.
The first problem is that, fundamentally, a photon in the Newtonian sense doesn't react or change based on the density of other photons around. So using a density field and trying to light to follow the classic Navier-Stokes style solutions (which is what you're trying to do, based on the density field explanation you gave) would result in incorrect results. It would also, given enough iterations, result in complete entropy over the scene, which is also not what happens to light.
Even if you were to get rid of the density problem, you're still left with the the problem of multiple photons going different directions in the same cell, which is required for global illumination and diffuse lighting.
So, stripping away the problem portions of your idea, what you're left with is a particle system for photons :P
Now, to be fair, sudo-particle systems are currently used for global illumination solutions. This type of thing is called Photon Mapping, but it's only simple to implement a direct lighting solution using it :P
Greetings,
I'm working on a game project that uses a 3D variant of hexagonal tile maps. Tiles are actually cubes, not hexes, but are laid out just like hexes (because a square can be turned to a cube to extrapolate from 2D to 3D, but there is no 3D version of a hex). Rather than a verbose description, here goes an example of a 4x4x4 map:
(I have highlighted an arbitrary tile (green) and its adjacent tiles (yellow) to help describe how the whole thing is supposed to work; but the adjacency functions are not the issue, that's already solved.)
I have a struct type to represent tiles, and maps are represented as a 3D array of tiles (wrapped in a Map class to add some utility methods, but that's not very relevant).
Each tile is supposed to represent a perfectly cubic space, and they are all exactly the same size. Also, the offset between adjacent "rows" is exactly half the size of a tile.
That's enough context; my question is:
Given the coordinates of two points A and B, how can I generate a list of the tiles (or, rather, their coordinates) that a straight line between A and B would cross?
That would later be used for a variety of purposes, such as determining Line-of-sight, charge path legality, and so on.
BTW, this may be useful: my maps use the (0,0,0) as a reference position. The 'jagging' of the map can be defined as offsetting each tile ((y+z) mod 2) * tileSize/2.0 to the right from the position it'd have on a "sane" cartesian system. For the non-jagged rows, that yields 0; for rows where (y+z) mod 2 is 1, it yields 0.5 tiles.
I'm working on C#4 targeting the .Net Framework 4.0; but I don't really need specific code, just the algorithm to solve the weird geometric/mathematical problem. I have been trying for several days to solve this at no avail; and trying to draw the whole thing on paper to "visualize" it didn't help either :( .
Thanks in advance for any answer
Until one of the clever SOers turns up, here's my dumb solution. I'll explain it in 2D 'cos that makes it easier to explain, but it will generalise to 3D easily enough. I think any attempt to try to work this entirely in cell index space is doomed to failure (though I'll admit it's just what I think and I look forward to being proved wrong).
So you need to define a function to map from cartesian coordinates to cell indices. This is straightforward, if a little tricky. First, decide whether point(0,0) is the bottom left corner of cell(0,0) or the centre, or some other point. Since it makes the explanations easier, I'll go with bottom-left corner. Observe that any point(x,floor(y)==0) maps to cell(floor(x),0). Indeed, any point(x,even(floor(y))) maps to cell(floor(x),floor(y)).
Here, I invent the boolean function even which returns True if its argument is an even integer. I'll use odd next: any point point(x,odd(floor(y)) maps to cell(floor(x-0.5),floor(y)).
Now you have the basics of the recipe for determining lines-of-sight.
You will also need a function to map from cell(m,n) back to a point in cartesian space. That should be straightforward once you have decided where the origin lies.
Now, unless I've misplaced some brackets, I think you are on your way. You'll need to:
decide where in cell(0,0) you position point(0,0); and adjust the function accordingly;
decide where points along the cell boundaries fall; and
generalise this into 3 dimensions.
Depending on the size of the playing field you could store the cartesian coordinates of the cell boundaries in a lookup table (or other data structure), which would probably speed things up.
Perhaps you can avoid all the complex math if you look at your problem in another way:
I see that you only shift your blocks (alternating) along the first axis by half the blocksize. If you split up your blocks along this axis the above example will become (with shifts) an (9x4x4) simple cartesian coordinate system with regular stacked blocks. Now doing the raytracing becomes much more simple and less error prone.