I'm working in C++ with large voxel grids in a scientific context and I'm trying to decide, which library to use. Only a fraction of the voxel grid holds values - but might be several per voxel (e.g. struct), which are determined by raytracing. I'm not trying to render anything, but I have to determine the potential number of rays passing though the entire target area, thus an awful lot of ray-box computations will have to be caluculated and preferebly very fast...
So far, I found
OpenVDB http://www.openvdb.org/
Field3d http://sites.google.com/site/field3d/
The latter appeals a bit more, because it seems simpler/easier to use.
My question is: Which of them would be more suited if put to use in tasks, which are not aimed at rendering/visualization? Which one is faster/better when computing a lot of ray-box-intersections (no viewpoint-dependent culling possible)? Suggestions, anyone?
In any case, I want to use an existing C++ library and not write a kdTree/Octree etc. myself. Don't have the time for inventing the wheel anew.
I would advise
OpenSceneGraph
Ogre3D
VTK
I have personally used the first two. However, VTK is also a popular alternative. All three of them support voxel based rendering.
Related
I have been looking for methods to register (align) organized point clouds with normal information.
I could only find generic point cloud registration methods (for example in PCL).
I am using Microsoft Kinect to get my point clouds, but the problem is that they are quite big.
What I would like to know:
Is there are fast ways to register organized point clouds?
Are there down-sampling methods that are very fast (and may also
be using the fact that the point clouds are organized)?
I was also thinking about using OpenCV filters, since an organized
point cloud could be though of as an image with gray values (2D matrix with depth values). For example using the openCV resize method on the matrix, and some derivative type filters (because edges are important for me in the scene). Is that a good idea?
Also, down-sampling looks like a data-parallel problem, which could be a great candidate for GPU implementation. Do you know about any such implementation?
What I have done so far is the following.
- Several down-sampling methods (Random, Voxel-based, Uniform), but the problem with all of them is that they all took a lot of time (in PCL). Best was Voxel-based.
- Then did ICP, which ran pretty fast and accurate enough for me on the down-sampled point clouds.
So for me, currently, a good solution would be a fast way of down-sampling my point clouds. For example a GPU-based implementation for it.
Thinking of an organized point cloud as an image with greyvalues (simple 2D matrix) turns out to be a good idea.
Downsampling methods for 2D matrices implemented on GPU are available in, for example, OpenCV cuda.
Also, it is easy to implement your own fast downsampling methods on 2D matrices, depending on how important accuracy is. For example, just simply take every kth element. You can do, if needed, averaging at these elements to blur, or derivative type filters to sharpen (edge enhancement). You can come up with special picking methods, depending on information about the frames (e.g. if you know your objects tend to be in the center, then you can pick more points around the area).
All these three above will give faster results and probably "more-tuned" to your problem (especially #3). "More-tuned" implies less robust.
I'm trying to make a game or 3D application using openGL. The game/program will have many objects in them and drawn to the screen(around 7000 of them). When I render them, I would need to calculate the distance between the camera and the object and sort them in order to correctly render the objects within the scene. Knowing this, what is the best way to sort them? I really want the sorting to be done really fast, but I've heard there are "trade off" for them, so what algorithm should I use to get the best performance out of it?
Any help would be greatly appreciated.
Edit: a lot of people are talking about the z-buffer/depth buffer. This doesn't work in some cases like a few people talked about. This is why I asked this question.
Sorting by distance doesn't solve the transparency problem perfectly. Consider the situation where two transparent surfaces intersect and each has a part which is closer to you. Perhaps rare in games, but still something to consider if you don't want an occasional glitched look to your renderer.
The better solution is order-independent transparency. With the latest graphics hardware supporting atomic operations, you can use an A-buffer to do this with little memory overhead and in a single pass so it is pretty efficient. See for example this article.
The issue of sorting your scene is still a valid one, though, even if it isn't for transparency -- it is still useful to sort opaque objects front to back to to allow depth testing to discard unseen fragments. For this, Vaughn provided the great solution of BSP trees -- these have been used for this purpose for as long as 3D games have been around.
Use http://en.wikipedia.org/wiki/Insertion_sort which has O(n) complexity for nearly sorted arrrays.
In your case by exploiting temporal cohesion insertion sort gives fastest results.
It is used for http://en.wikipedia.org/wiki/Sweep_and_prune
From link above:
In many applications, the configuration of physical bodies from one time step to the next changes very little. Many of the objects may not move at all. Algorithms have been designed so that the calculations done in a preceding time step can be reused in the current time step, resulting in faster completion of the calculation.
So in such cases insertion sort is best(or similar sorts with O(n) at best case)
I have a device to acquire XRay images. Due to some technical constrains, the detector is made of heterogeneous pixel size and multiple tilted and partially overlapping tiles. The image is thus distorted. The detector geometry is known precisely.
I need a function converting these distorted images into a flat image with homogeneous pixel size. I have already done this by CPU, but I would like to give a try with OpenGL to use the GPU in a portable way.
I have no experience with OpenGL programming, and most of the information I could find on the web was useless for this use. How should I proceed ? How do I do this ?
Image size are 560x860 pixels and we have batches of 720 images to process. I'm on Ubuntu.
OpenGL is for rendering polygons. You might be able to do multiple passes and use shaders to get what you want but you are better off re-writing the algorithm in OpenCL. The bonus then would be you have something portable that will even use multi core CPUs if no graphics accelerator card is available.
Rather than OpenGL, this sounds like a CUDA, or more generally GPGPU problem.
If you have C or C++ code to do it already, CUDA should be little more than figuring out the types you want to use on the GPU and how the algorithm can be tiled.
If you want to do this with OpengGL, you'd normally do it by supplying the current data as a texture, and writing a fragment shader that processes that data, and set it up to render to a texture. Once the output texture is fully rendered, you can retrieve it back to the CPU and write it out as a file.
I'm afraid it's hard to do much more than a very general sketch of the overall flow without knowing more about what you're doing -- but if (as you said) you've already done this with CUDA, you apparently already have a pretty fair idea of most of the details.
At heart what you are asking here is "how can I use a GPU to solve this problem?"
Modern GPUs are essentially linear algebra engines, so your first step would be to define your problem as a matrix that transforms an input coordinate < x, y > to its output in homogenous space:
For example, you would represent a transformation of scaling x by ½, scaling y by 1.2, and translating up and left by two units as:
and you can work out analogous transforms for rotation, shear, etc, as well.
Once you've got your transform represented as a matrix-vector multiplication, all you need to do is load your source data into a texture, specify your transform as the projection matrix, and render it to the result. The GPU performs the multiplication per pixel. (You can also write shaders, etc, that do more complicated math, factor in multiple vectors and matrices and what-not, but this is the basic idea.)
That said, once you have got your problem expressed as a linear transform, you can make it run a lot faster on the CPU too by leveraging eg SIMD or one of the many linear algebra libraries out there. Unless you need real-time performance or have a truly immense amount of data to process, using CUDA/GL/shaders etc may be more trouble than it's strictly worth, as there's a bit of clumsy machinery involved in initializing the libraries, setting up render targets, learning the details of graphics development, etc.
Simply converting your inner loop from ad-hoc math to a well-optimized linear algebra subroutine may give you enough of a performance boost on the CPU that you're done right there.
You might find this tutorial useful (it's a bit old, but note that it does contain some OpenGL 2.x GLSL after the Cg section). I don't believe there are any shortcuts to image processing in GLSL, if that's what you're looking for... you do need to understand a lot of the 3D rasterization aspect and historical baggage to use it effectively, although once you do have a framework for inputs and outputs set up you can forget about that and play around with your own algorithms in shader code relatively easily.
Having being doing this sort of thing for years (initially using Direct3D shaders, but more recently with CUDA) I have to say that I entirely agree with the posts here recommending CUDA/OpenCL. It makes life much simpler, and generally runs faster. I'd have to be pretty desperate to go back to a graphics API implementation of non-graphics algorithms now.
I need to represent a planar graph structure, i.e., a division of part of the plane into polygons so that I can easily find a polygon's neighbors etc (like on a map). What is the best library to use? ArcObjects? CGAL (2D arrangements)? Anything else?
I use C++ under Windows.
If you're interested in speed or reliability, stay away from ArcObjects. ArcMap is a neat application, and there's good reasons to write plug-ins for it. But ArcObjects is not a good programming library for general purpose GIS use.
I would look at QGIS and see what they use under the hoods.
You could also look at GEOS. It might have some of the stuff you need
http://trac.osgeo.org/geos/
Actually - after looking at it a bit I think it could definitely suit your needs.
Does anyone have some useful beginner tutorials and code snippets for playing with basic geometric shapes and geometric proofs in code?
In particular something with the ability to easily create functions and recursively draw them on the screen. Additional requirements, but not absolute, support for Objective-C and basic window drawing routines for OS X and Cocoa.
A specific question how would one write a test to validate that a shape is in fact a square, triangle, etc. The idea being that you could draw a bunch of shapes, fit them together and test and analyze the emergent shape that arises from the set of sub shapes.
This is not a homework question. I am not in school. Just wanted to experiment with drawing code and geometry. And looking for an accessible way to play and experiment with shapes and geometry programming.
I am open to Java and Processing, or Actionscript/Haxe and Flash but would also like to use Objective C and Xcode to build projects as well.
What I am looking for are some clear tutorials to get me started down the path.
Some specific applications include clear examples of how to display for example parts of a Cantor Set, Mandelbrot Set, Julia set, etc...
One aside, I was reading on Wikipedia about the "Russell's Paradox". And the wiki article stated:
Let us call a set "abnormal" if it is
a member of itself, and "normal"
otherwise. For example, take the set
of all squares. That set is not itself
a square, and therefore is not a
member of the set of all squares. So
it is "normal". On the other hand, if
we take the complementary set that
contains all non-squares, that set is
itself not a square and so should be
one of its own members. It is
"abnormal".
The point about squares seems intuitively wrong to me. All the squares added together seem to imply a larger square. Obviously I get the larger paradox about sets. But what I am curious about is playing around with shapes in code and analyzing them empirically in code. So for example a potential routine might be draw four squares, put them together with no space between them, and analyze the dimensions and properties of the new shape that they make.
Perhaps even allowing free hand drawing with a mouse. But for now just drawing in code is fine.
If you're willing to use C++ I would recommend two libraries:
boost::GGL generic geometry library handles lots of geometric primitives such as polygons, lines, points, and so forth. It's still pretty new, but I have a feeling that it's going to be huge when it's officially added into boost.
CGAL, the Computational Geometry Algorithms Library: this thing is huge, and will do almost anything you'll ever need for geometry programming. It has very nice bindings for Qt as well if you're interested in doing some graphical stuff.
I guess OpenGL might not be the best starting point for this. It's quite low-level, and you will have to fight with unexpected behavior and actual driver issues. If you emphasize the "playing" part, go for Processing. It's a programming environment specifically designed to play with computer graphics.
However, if you really want to take the shape testing path, an in-depth study of computer vision algorithms in inevitable. On the other hand, if you just want to compare your shapes to a reference image, without rotation, scaling, or other distortions, the Visual Difference Predictor library might help you.
I highly recommend NeHe for any beginner OpenGL programmer, once you complete the first few tutorials you should be able to have fun with geometry any way you want.
Hope that helps