[vtk-developers] vtkPointCloud remote module

Ken Martin ken.martin at kitware.com
Sat Jan 30 11:26:09 EST 2016


Cool.  I was thinking you would piggyback on an existing vtkXML*Writer as
they have a ton of functionality already built in. I'm not a XML*Writer
expert but they definitely support a lot of cool features including zlib
compression, pieces, multiple files.

Ken


On Sat, Jan 30, 2016 at 8:48 AM, Will Schroeder <will.schroeder at kitware.com>
wrote:

> Okay I have a quick and dirty design for "file" format and algorithmic
> approach that I'll start implementing shortly. We'll clean it up with time.
> Any feedback is welcome.
>
> The data file format has three basic logical parts, which could be written
> into separate files or one file, whatever. 1) metadata, 2) offsets, and 3)
> sorted points.
>
> The key idea is that the points are in sorted order, beginning with level
> 0 root node, followed by level 1 bins (8 bins) and their points, and level
> 2 bins (64 bins) and their points, and so on. The points are just a
> contiguous array of x-y-z, x-y-z, of type float or double (user specified),
> etc. Data attributes could be stored in similar fashion (all easily
> changeable depending on what you prefer). Since the number of points in
> each bin is variable and may even be zero, this is where the offsets come
> into play. (Note that points are not repeated, and statistically sampled as
> you suggest ~1/(total number of bins)*NumberOfPoints points in each bin.)
>
> The offsets are integral values that simply refer to a position in the
> sorted points array corresponding to the beginning of each bin. So (level
> 0, bin 0), (level 1, bin 0), (1,1), (1,2), (1,3), (1,4), (1,5), (1,6),
> (1,7), (2,0), (2,1), ... you get the idea. For your example of a 3-level
> octree, there would be 73 offset values (or T=73 total bins). Note that if
> offset_i == offset_(i+1) then there are zero points in the bin referred to
> by offset_i. We can also represent the offsets with different integral
> types depending on the number of points (to save memory).
>
> The metadata contains something like (assuming multiple separate files,
> which of course can be memory mapped, etc):
> NumberOfPoints #npts
> NumberOfLevels #numLevels
> Divisions 2 2 2
> Bounds (xmin,xmax,ymin,ymax,zmin,zmax)
> Points type "points.file"
> Offsets type "offsets.file"
> Array type numComp "scalars.file"
> Array type numComp "vectors.file"
>
> Note that the Divisions are variable, the structure does not have to be an
> octree. This is useful to produce bins that are closer to uniform shape, or
> even create a 2.5D, sorta flat binning tree (e.g. z-divisions always == 1).
>
> Algorithmic approach: (this can easily be threaded):
> For every point p_i in the input point cloud, generate a random number r
> (0<=r<1). Assume that there are T total bins.
> The probability (assuming an octree) that p_i is in level 0: is 1/T; in
> level 1: 8/T; in level 2: 64/T and so on. Segment the range [0,1) into
> proportional subranges that r maps into. Thus r will randomly select which
> level of the tree a point belongs in.
>
> Once p_i is assigned a level, compute a hash index h_i which consists of
> the (i,j,k) bin index added to T_l, there T_l is the total number of bins
> at the beginning of level l. This hash index is the key to get the sort in
> the right order; using the level information is a way to segment the bins
> from different levels into contiguous runs.
>
> Now sort the points based on this hash index. The sort is where most of
> the work is done and we'll use vtkSMPTools::Sort(). This produces a sorted
> points list. Next create the offsets array by running through the sorted
> hash indices, etc. (I've done this before in vtkStaticPointsLocator, it's
> easy to do, and can even be done in parallel.)
>
> From the mapper point of view: knowing the bounds, divisions, current
> level, and (i,j,k) bin index it is possible to construct a local bounding
> box for each bin. Then there is direct access to the list of points in each
> bin (through the offsets). And of course since this is a hierarchy of
> uniform bins, you can easily perform view culling etc. and choose the
> appropriate level for LODs.
>
> That's it in a nutshell. Unfortunately I've got lots of pointy-haired boss
> stuff to do so this might take a bit to complete, but I'd really like to
> get a prototype class written this week
> (vtkPointCloud/vtkHierarchicalBinningFilter), it's got me revved up :-)
> Initially I'll have this class build the data structures, with a special
> back-door method to write the data out. Later on we'll decide if we need to
> separate this backdoor IO into a separate class, etc.
>
> Best,
> W
>
>
> On Fri, Jan 29, 2016 at 12:15 PM, Ken Martin <ken.martin at kitware.com>
> wrote:
>
>> Thanks Will. I promise I'll write the mapper :-) The PTS reader is a
>> simple ascii X Y Z R G B type format that I usually immediately convert to
>> VTK XML format as that is far faster and more compact. So unfortunately PTS
>> is not it. I am thinking a vtkXMLPolyDataWriter subclass that adds some
>> bounding box metadata.
>>
>> Ken
>>
>> On Fri, Jan 29, 2016 at 11:08 AM, Will Schroeder <
>> will.schroeder at kitware.com> wrote:
>>
>>> Ken-
>>>
>>> I am totally with you. I am writing some simple stuff at the moment like
>>> VoxelGrid as sort of a "drop-in" replacements for PCL workflows; mostly to
>>> get my head around the challenges and serve as a stop gap until our better
>>> stuff comes along. I really like your idea and I do plan to implement this;
>>> it's really not too hard to do from what I understand and given the pieces
>>> available in VTK.
>>>
>>> So I'll wrap up this simple VoxelGrid and then take a crack at the beast
>>> you've envisioned. The two major pieces seems to be 1) create a class that
>>> builds the hierarchical structure, and 2) write a reader/writer pair that
>>> can perform associated IO. In an earlier email you mentioned a PTS reader
>>> that you made improvement to; is this a good exemplar data format or do you
>>> have a better starting point?
>>>
>>> It seems I have a homework assignment for the weekend :-)
>>>
>>> Best,
>>> W
>>>
>>> On Fri, Jan 29, 2016 at 10:42 AM, Ken Martin <ken.martin at kitware.com>
>>> wrote:
>>>
>>>> Nice, can I make a specific request Will? :-) Part of what I want to do
>>>> for large point clouds is something like the following:
>>>>
>>>> 1) Open a VTK multipiece file and read in the bounding boxes of the
>>>> pieces (but not the data)
>>>>
>>>> 2) Read in the first piece and use it for rendering
>>>>
>>>> 3) In the background read in more pieces, as they are loaded make them
>>>> available to the mapper
>>>>
>>>> 4) The mapper based on the current camera parameters and bounding boxes
>>>> of the pieces intelligently selects what pieces to render. This provides a
>>>> happy fast interactive experience leading to world peace.
>>>>
>>>> For this to work well my thought was to have the pieces be broken up in
>>>> a special way sort of like an octree but a spatial hash etc would be just
>>>> as good as long as it is hierarchical and structured. Think of breaking up
>>>> the volume into 1 + 8 + 64 pieces. The first piece contains ~1/73 of the
>>>> data covering the entire bounding box. The next eight pieces also each
>>>> contain  about 1/73 of the data each constrained by their octant of the
>>>> bounding box. Same idea for the next 64 boxes, they are just one level
>>>> further down.  This would work really well for a smart mapper providing
>>>> fast first render plus fast LOD/subsequent renders. I can implement 1-4
>>>> pretty quickly.
>>>>
>>>> But .... for it to work I need someone to create the 73 piece file the
>>>> right way. (it does not have to be 73, and clearly some of those 73 will be
>>>> empty, it just needs to be hierarchical and structured so that a group of
>>>> pieces can be represented at a lower level of detail by some other piece)
>>>> My gut feeling was to have the LOD pieces use actual points of the dataset
>>>> (not centroids or similar) that way as more pieces are loaded we are just
>>>> providing more detail, not replacing fake data (centroids) with real data.
>>>> But really either approach is pretty easy to implement in the mapper. The
>>>> latter approach just means the entire dataset footprint is larger because
>>>> some of the points are not part of the full res dataset because you
>>>> generated them.
>>>>
>>>> I could be totally off base but that was my gut feeling on rendering >
>>>> 2GB point clouds in a nice zippy manner.
>>>>
>>>> TLDR: I want someone to write a filter/writer subclass to create a
>>>> special 73 piece vtk file :-)
>>>>
>>>> Ken
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Fri, Jan 29, 2016 at 10:06 AM, Will Schroeder <
>>>> will.schroeder at kitware.com> wrote:
>>>>
>>>>> Geoff-
>>>>>
>>>>> I knocked out a vtkVoxelGrid last night, it seems to work great. It's
>>>>> threaded and seems to be fast.
>>>>>
>>>>> Question for you before I push the work to the repository: averaging
>>>>> points in each bin provides a nice subsampled point position. But what do
>>>>> you think we should do for attributes (e.g., scalars, vector, etc.)? These
>>>>> could be averaged too. There are however other options like finding the
>>>>> closest point to the subsampled point and using those attribute values, or
>>>>> if you want to get really fancy, using an interpolation kernel to
>>>>> interpolate to the subsampled point.
>>>>>
>>>>> Thoughts?
>>>>> W
>>>>>
>>>>> On Thu, Jan 28, 2016 at 10:03 AM, Will Schroeder <
>>>>> will.schroeder at kitware.com> wrote:
>>>>>
>>>>>> Thanks for the feedback. I have some downsampling filters in the
>>>>>> works now, I'll let you know when I have something ready.
>>>>>>
>>>>>> BTW we are on a similar path. PCL is awesome, but we have some common
>>>>>> workflows that would be better served with more compact software
>>>>>> environments, and with minimal IO and/or data transfer. So we're trying to
>>>>>> knock of a small kernel of capability to achieve this.
>>>>>>
>>>>>> Best,
>>>>>> W
>>>>>>
>>>>>> On Thu, Jan 28, 2016 at 9:56 AM, Geoff Wright <gpwright at gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>>> Hi Will,
>>>>>>>
>>>>>>> This is good to see.  I'm currently using VTK to generate surfaces
>>>>>>> from some point cloud data.  I have some initial pre processing steps that
>>>>>>> I use PCL (point cloud library) for, and then a vtk stage that converts PCL
>>>>>>> point cloud into vtkPolyData/vtkPoints.  It would be great to
>>>>>>> eliminate the PCL dependency and use exclusively vtk.  My point
>>>>>>> cloud data grows very large over time with a lot of redundant points so its
>>>>>>> very important to downsample them onto uniform spacing (
>>>>>>> http://docs.pointclouds.org/trunk/classpcl_1_1_voxel_grid.html )
>>>>>>> before processing them in vtk.  Would it make sense to add something like
>>>>>>> this to your library?
>>>>>>>
>>>>>>> Geoff
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Thu, Jan 28, 2016 at 9:12 AM Will Schroeder <
>>>>>>> will.schroeder at kitware.com> wrote:
>>>>>>>
>>>>>>>> FYI- I have committed an initial set of filters for performing
>>>>>>>> point cloud processing. Any feedback or suggestions are welcome as this is
>>>>>>>> an initial prototype. The work is currently available as a remote module to
>>>>>>>> VTK (vtkPointCloud) via this repository:
>>>>>>>> https://gitlab.kitware.com/vtk/point-cloud.git
>>>>>>>>
>>>>>>>> A couple of notes:
>>>>>>>> + Right now I am using vtkPolyData to represent the point cloud via
>>>>>>>> a vtkPoints instance. There are no vtkVertex, vtkPolyVertex cells created
>>>>>>>> to save on memory.
>>>>>>>> + The classes will process as input any vtkPointSet dataset
>>>>>>>> + There is a general framework for filtering point clouds via the
>>>>>>>> class vtkPointCloudFilter. Besides their filtered cloud output, these
>>>>>>>> filters also have an optional, second output which contains any points
>>>>>>>> removed from the input.
>>>>>>>> + Current filters include vtkRadiusOutlierRemoval,
>>>>>>>> vtkStatisticalOutlierRemoval, vtkExtractPoints (extract points using an
>>>>>>>> implicit function). Some of  these names are inspired by PCL
>>>>>>>> <http://pointclouds.org/> names.
>>>>>>>> + All filters are threaded using vtkSMPTools using a threaded
>>>>>>>> locator (vtkStaticPointLocator) so I believe that this is relatively fast,
>>>>>>>> although I have not done much testing.
>>>>>>>> + I'm using vtkPointGaussianMapper in the tests, a class that Ken
>>>>>>>> wrote that is very fast.
>>>>>>>>
>>>>>>>> As usual comments and suggestions are requested. In particular any
>>>>>>>> suggestions for other filters to write are welcome (to round out some of
>>>>>>>> the core functionality). The repository is in flux as I try crazy ideas and
>>>>>>>> try to educate myself, so be forewarned.
>>>>>>>>
>>>>>>>> Best,
>>>>>>>> W
>>>>>>>>
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> Powered by www.kitware.com
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>>>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> William J. Schroeder, PhD
>>>>>> Kitware, Inc. - Building the World's Technical Computing Software
>>>>>> 28 Corporate Drive
>>>>>> Clifton Park, NY 12065
>>>>>> will.schroeder at kitware.com
>>>>>> http://www.kitware.com
>>>>>> (518) 881-4902
>>>>>>
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> William J. Schroeder, PhD
>>>>> Kitware, Inc. - Building the World's Technical Computing Software
>>>>> 28 Corporate Drive
>>>>> Clifton Park, NY 12065
>>>>> will.schroeder at kitware.com
>>>>> http://www.kitware.com
>>>>> (518) 881-4902
>>>>>
>>>>> _______________________________________________
>>>>> Powered by www.kitware.com
>>>>>
>>>>> Visit other Kitware open-source projects at
>>>>> http://www.kitware.com/opensource/opensource.html
>>>>>
>>>>> Search the list archives at:
>>>>> http://markmail.org/search/?q=vtk-developers
>>>>>
>>>>> Follow this link to subscribe/unsubscribe:
>>>>> http://public.kitware.com/mailman/listinfo/vtk-developers
>>>>>
>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> Ken Martin PhD
>>>> Chairman & CFO
>>>> Kitware Inc.
>>>> 28 Corporate Drive
>>>> Clifton Park NY 12065
>>>> 518 371 3971
>>>>
>>>> This communication, including all attachments, contains confidential
>>>> and legally privileged information, and it is intended only for the use of
>>>> the addressee.  Access to this email by anyone else is unauthorized. If you
>>>> are not the intended recipient, any disclosure, copying, distribution or
>>>> any action taken in reliance on it is prohibited and may be unlawful. If
>>>> you received this communication in error please notify us immediately and
>>>> destroy the original message.  Thank you.
>>>>
>>>
>>>
>>>
>>> --
>>> William J. Schroeder, PhD
>>> Kitware, Inc. - Building the World's Technical Computing Software
>>> 28 Corporate Drive
>>> Clifton Park, NY 12065
>>> will.schroeder at kitware.com
>>> http://www.kitware.com
>>> (518) 881-4902
>>>
>>
>>
>>
>> --
>> Ken Martin PhD
>> Chairman & CFO
>> Kitware Inc.
>> 28 Corporate Drive
>> Clifton Park NY 12065
>> 518 371 3971
>>
>> This communication, including all attachments, contains confidential and
>> legally privileged information, and it is intended only for the use of the
>> addressee.  Access to this email by anyone else is unauthorized. If you are
>> not the intended recipient, any disclosure, copying, distribution or any
>> action taken in reliance on it is prohibited and may be unlawful. If you
>> received this communication in error please notify us immediately and
>> destroy the original message.  Thank you.
>>
>
>
>
> --
> William J. Schroeder, PhD
> Kitware, Inc. - Building the World's Technical Computing Software
> 28 Corporate Drive
> Clifton Park, NY 12065
> will.schroeder at kitware.com
> http://www.kitware.com
> (518) 881-4902
>



-- 
Ken Martin PhD
Chairman & CFO
Kitware Inc.
28 Corporate Drive
Clifton Park NY 12065
518 371 3971

This communication, including all attachments, contains confidential and
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