Trimble Business Center

I have used many point cloud toolsets, and am now using TBC. One of the main tasks we do is make a TIN surface from ground classified point cloud region. Of course, if you use all points you get too many triangles, and that process of thinning down the points, but not smoothing the surface too much is a big deal when you have curbs and hardscape involved.

So in TBC, the only options of thinning down points is by sampling. The two options are not clear to me though.

I am wondering for the spatial sampling: Is the sampled point the average of all the points within the sample area size? Or is it a point taken in the middle of the area based on immediately surrounding points?

Also, does the random sampling method work the same?

Really, this kind of sampling is not good enough for the task at hand, as it does not distinguish between "important" points, and those that form a slightly varying plane. Civil's want the best and smallest set of triangles to describe the ground.

We want big triangles for flat areas, and little tris for areas that vary a bunch.

TBC is missing this kind of analysis, so I normally use the Carlson pt cloud tools to make the TIN. So workflow is TBC to classify and clean the ground region, and Carlson to make the "optimized" TIN. Its not great though. The Carlson tool needs to make tris smaller in some areas, and larger in others, but at least it does an ok job.

Anyway, I wanted to understand the sampling as it has to at least do an averaging or its not that useful to me.

thanks

James

I am just in the process of uploading my Training Tools from the PUG conference 2 weeks ago on this subject - I enclose the Exercise document here - if you read through it it is hopefully a step by step guide on how to do this

These Links will also help

Link 1

Link 2

Link 3

I hope these help along with the Document. There is an embedded video in the links that shows the process and how to use the settings to model the Point Clouds

Alan

The above materials should help you to work through managing your point clouds - the Variable Density Modeling is likely the most important information relating to your question, however used in combination with the Sampling tools you can likely improve it further.

The Sampling tools offer two methods today to sample a Point Cloud Region

The Spatial Algorithm is trying to find a near point to your Spatial Sampling parameter - ie if you say every 2' then it is looking for the nearest point to your 2' pacing.

The Random sampling if you say you want 1000000 points out of a 10,000,000 Point Point Cloud then it will effectively extract the 10th point from 10 points based on order of measurement.

Neither method is looking at the shape of the "surface" as it extracts the point data

My method of working is as follows

1) Get your scans into the Project and aggregate them into a Point Cloud Region called e.g. August Survey

2) Bound the Point Cloud to the area that you are working in and select all the data outside and move it to a new point cloud region called August - Not Needed or similar

3) You can use the Classify Regions or Extract Ground functions to try and eliminate Tree / Shrub canopy and to try to break out Buildings, Poles, Vegetation etc.

4) Use the Polygon Select method combined with Limit Box to select and move Bad Data eg Vehicles, People, Noise, Piles of pipe, and other things you dont need into the Not Needed Point Cloud Region

5) After all those steps you are left with the Point Data that you will use to form your surfaces.

6) Within the remaining data, you may want to create an extra Point Cloud Region, and move data into that selected by Polygon Select method that you need to model at Higher Density than other areas that you will be happy with lower density - you can create regions of Low, Medium and High density need as you see fit

7) Set your Support - Options - Point Clouds settings for the number of points in a surface - refer to the exercise details that shows how Variable Density Modeling can be used (this is the secret in BC-HCE to getting increased Fidelity where you need it and Lower Fidelity where you dont, and trying to keep your surfaces as small as possible but as accurate as you need them.

8) Build up your surface by adding Point Cloud regions in incremental steps - remember that each Region you add after the surface is first created will extract however many points you have specified in Support - Options - Point Clouds - and in this way you can change the density of points. It is sometimes worth looking at the number of points in each of your regions to determine what you think may be required to create the model that you want to create.

With experimentation, I have found this to work really well and I can typically get what the end user wants in a surface model using these methods. Having said that I am typically working with Civil Earthmovers and Rock Excavation teams and they have different needs to a pure land surveyor

You can also look at the Feature Extract methods if you need to pull out feature lines to assist forming good surfaces along Features like Flow Lines or top of curb etc.

Polygon select in Plan or 3D view (3D especially) is a great tool to islolate areas like curb or barier or retaining wall that you want to model at higher density than areas like the Pavement or embankment areas

Hope that this helps

Alan

Hi Alan,

Thanks for the detailed response.

The problem with manual picking of areas is I don't know what the areas should be. There may be cases where I do, like a pavement area of a road, but the idea is the computer analyzes things and likely varies the simplification of original triangles in several passes to get to the desired triangle count limit.

The Carlson tool does that, but does not give much control over how much simplification is performed.

So a manual process is simply not practical - same for if you said to manually classify point cloud data. I would say this goes for all types of "ground modeling" work, and I'm sure the mining guys would love to have that feature. Carlson would say their main audience is contractors and miners, and those customers are actually more willing to take the triangle simplification than road design people who want sharp corners for road undercut or other things.

All I am saying is you have an opportunity to make a lot of people happy by pursuing such a feature. No one else seems to have done a great job of it, yet every civil discovering drone and scanner point cloud data wants it.

The automatic curb edge tool is close to what we want, and helpful, but those kinds of features are typically traced in plan first using ortho photo as its higher res than a point cloud. Then we assign elevations from the point cloud. We can't have a curb wandering left and right as seen in plan view. Also, the elevations are typically coming from points on one side of the curb only. I would want the tool to look at points 6" to one side, average those into a profile line, and that becomes the curb profile. The current workaround is I take your 3d line which wanders in plan view some, and project its profile to my clean 2d curb line. We have our own toolset to do that in autocad.

Both those features are high fruit on the tree. You won't just whip them out. If I were a C++ guy, I would be making my own tools using the PCL library. Its open source so you might look to it for ideas though I am sure your developers know about it and maybe even use it in TBC. Mesh simplification is an art, and I can think of several ways to approach it.

thanks