Transcript
00:01
NARRATOR: Welcome to the continuation of the Managing
00:03
Point Cloud Data in Recap course.
00:06
This objective is using structured point cloud data,
00:09
and it is the second objective in the course.
00:13
From the previous objective, we learned
00:15
that there were two different types of scan data
00:17
that we can use to represent our existing conditions.
00:21
We have structured and non-structured.
00:24
Using structured data for infrastructure projects
00:28
is unique.
00:29
Typically, non-structured data is
00:31
what we use to define existing topography.
00:35
However, structured scans can provide
00:37
additional detail that help define the existing conditions.
00:42
The unique features that often need high detail
00:45
and can be represented using structured scan data
00:49
include intersections and roadway features, bridges,
00:54
utilities, significant buildings and other structures.
00:58
Structured and non-structured data
00:60
can be combined for excellent existing conditions
01:04
representations.
01:06
Using structured data to scan areas of detail
01:10
can be done from one or many scan locations.
01:14
Structured scan data has more manipulation features
01:17
and recap, including manual registration and alignment
01:21
of the scans, adding survey control points,
01:25
cleaning up to remove noise, and they can
01:28
be viewed in the RealView mode.
01:31
Some forms of structured data and recap
01:34
will have a RealView enabled, and
01:37
the individual scan locations appear
01:39
as 3D orbs, sometimes called mirror balls.
01:44
When clicking on an orb, the view
01:46
changes to the photorealistic view of the original scan.
01:52
Now let's take a look at the best of all worlds,
01:54
and this is combining structured and unstructured data,
01:58
and we have many static scans that we're
01:60
going to combine to detail the building inside and out.
02:04
But to get the surrounds, we're going
02:06
to use a drone to capture either light or photos that will
02:10
be converted into point clouds.
02:12
Here, we can see we're registering
02:14
the structured data.
02:16
After we register the structured data,
02:19
we'll locate it in the drone-captured unstructured
02:23
data, and we have a good full project.
02:30
Now that you know about scan data types,
02:32
we can look at a structured scan workflow.
02:37
In this example, we will import structured point cloud data
02:40
from a stationary scanner.
02:42
I'm going to drag and drop the files into recap.
02:46
I will review the default settings
02:48
for filtering and range and intensity clipping.
02:54
In the advanced settings, I will slide the decimation value
02:57
to 0, because this scan is not very dense.
03:01
And we will not set a coordinate system,
03:03
because this scan was done on assumed coordinates that
03:07
were arbitrarily set when the scan was done on site.
03:10
After import, we see from the icon
03:13
that looks like a scanner on a tripod
03:15
that these are structured data scans.
03:18
I'm going to manually register these five individual scans
03:21
by selecting on the bottom or top-right icon.
03:24
After fast forwarding, I see the five scan locations on the left
03:28
and the bird's eye top view in the upper right.
03:31
I start the registration by choosing
03:33
the first scan location, and the registration tips appear.
03:39
It's good to review the tips so you know where and how to pick
03:42
the points that will work to correlate from one scan
03:46
to the next.
03:47
I will look carefully to identify
03:49
similar features in each scan from the left side
03:53
to the right side, and I see the center of the manholes
03:56
will be a good pick.
04:02
Also note, I can make points survey points and assign
04:06
actual coordinate values to them if I have that information.
04:17
After setting the centers of the two manholes,
04:21
I want to find a point on a totally different plane
04:24
so I will zoom in, and I will find the green and white label
04:27
on the meter.
04:36
Now on the right panel, I will find a similar point to match.
04:42
After correlating three points from the right panel
04:45
to the left panel, we have a message telling us
04:48
we've found a match and we can merge the scans.
04:52
Once merged, I went to look at the results,
04:55
and even though the results are not perfect,
04:57
I'm going to approve them because I have a 100% point
05:01
correlation, and this is good enough for this example.
05:06
I will continue doing this for the remaining scans.
05:09
If I have five scans, I'm going to have
05:12
to match three points five different times
05:15
to get the full registration.
05:20
In the next comparison, I have matched three points,
05:23
and we'll merge the results and see that in this case,
05:26
there was a good match.
05:28
Now I will fast forward to finishing
05:31
with the last of the five scans.
05:33
I will also approve those results.
05:35
And now all of the scans are registered.
05:38
I can look at a quality report to see the entire match status.
05:43
And next, I will move to index the scans.
05:46
This will take a few minutes, so I will fast forward,
05:49
and once the scans are indexed, we will launch the project.
05:53
After launching a project made from structured points,
05:56
we see that there are five orbs, or mirror balls, one
06:01
for each of the scan locations.
06:04
If I select a mirror ball, it changes
06:06
to a panoramic scan view of that location.
06:10
I can spin around, and I can see the photorealistic visual
06:13
quality of that scan.
06:16
I want to use the measurement tool to check
06:18
the size across the pipes.
06:20
This will validate if I'm in the correct units
06:23
and in the correct scale.
06:25
After verifying the measurement, I
06:27
returned to the 3D view and the mirror balls reappear.
06:32
Now I will export this point cloud
06:34
so that I can use it in a variety of Autodesk
06:37
applications.
06:38
I do this from the scan location collection,
06:41
and I want to export this as an RCS file.
06:45
This file will include all the points of the point cloud.
06:49
We could see that there are other point cloud export
06:52
types, such as PTS and E57.
06:56
I will review the unified settings.
06:58
I accept the default value as this scan is not very dense,
07:02
and there is no advantage in decimating
07:05
any closely located points.
07:08
And finally, I select Unify the Project Scan,
07:11
and the output RCS file is created.
07:15
This completes this course objective.
07:18
And now we're ready for the third course objective,
07:21
Using Non-structured Point Cloud Data in Recap.
00:01
NARRATOR: Welcome to the continuation of the Managing
00:03
Point Cloud Data in Recap course.
00:06
This objective is using structured point cloud data,
00:09
and it is the second objective in the course.
00:13
From the previous objective, we learned
00:15
that there were two different types of scan data
00:17
that we can use to represent our existing conditions.
00:21
We have structured and non-structured.
00:24
Using structured data for infrastructure projects
00:28
is unique.
00:29
Typically, non-structured data is
00:31
what we use to define existing topography.
00:35
However, structured scans can provide
00:37
additional detail that help define the existing conditions.
00:42
The unique features that often need high detail
00:45
and can be represented using structured scan data
00:49
include intersections and roadway features, bridges,
00:54
utilities, significant buildings and other structures.
00:58
Structured and non-structured data
00:60
can be combined for excellent existing conditions
01:04
representations.
01:06
Using structured data to scan areas of detail
01:10
can be done from one or many scan locations.
01:14
Structured scan data has more manipulation features
01:17
and recap, including manual registration and alignment
01:21
of the scans, adding survey control points,
01:25
cleaning up to remove noise, and they can
01:28
be viewed in the RealView mode.
01:31
Some forms of structured data and recap
01:34
will have a RealView enabled, and
01:37
the individual scan locations appear
01:39
as 3D orbs, sometimes called mirror balls.
01:44
When clicking on an orb, the view
01:46
changes to the photorealistic view of the original scan.
01:52
Now let's take a look at the best of all worlds,
01:54
and this is combining structured and unstructured data,
01:58
and we have many static scans that we're
01:60
going to combine to detail the building inside and out.
02:04
But to get the surrounds, we're going
02:06
to use a drone to capture either light or photos that will
02:10
be converted into point clouds.
02:12
Here, we can see we're registering
02:14
the structured data.
02:16
After we register the structured data,
02:19
we'll locate it in the drone-captured unstructured
02:23
data, and we have a good full project.
02:30
Now that you know about scan data types,
02:32
we can look at a structured scan workflow.
02:37
In this example, we will import structured point cloud data
02:40
from a stationary scanner.
02:42
I'm going to drag and drop the files into recap.
02:46
I will review the default settings
02:48
for filtering and range and intensity clipping.
02:54
In the advanced settings, I will slide the decimation value
02:57
to 0, because this scan is not very dense.
03:01
And we will not set a coordinate system,
03:03
because this scan was done on assumed coordinates that
03:07
were arbitrarily set when the scan was done on site.
03:10
After import, we see from the icon
03:13
that looks like a scanner on a tripod
03:15
that these are structured data scans.
03:18
I'm going to manually register these five individual scans
03:21
by selecting on the bottom or top-right icon.
03:24
After fast forwarding, I see the five scan locations on the left
03:28
and the bird's eye top view in the upper right.
03:31
I start the registration by choosing
03:33
the first scan location, and the registration tips appear.
03:39
It's good to review the tips so you know where and how to pick
03:42
the points that will work to correlate from one scan
03:46
to the next.
03:47
I will look carefully to identify
03:49
similar features in each scan from the left side
03:53
to the right side, and I see the center of the manholes
03:56
will be a good pick.
04:02
Also note, I can make points survey points and assign
04:06
actual coordinate values to them if I have that information.
04:17
After setting the centers of the two manholes,
04:21
I want to find a point on a totally different plane
04:24
so I will zoom in, and I will find the green and white label
04:27
on the meter.
04:36
Now on the right panel, I will find a similar point to match.
04:42
After correlating three points from the right panel
04:45
to the left panel, we have a message telling us
04:48
we've found a match and we can merge the scans.
04:52
Once merged, I went to look at the results,
04:55
and even though the results are not perfect,
04:57
I'm going to approve them because I have a 100% point
05:01
correlation, and this is good enough for this example.
05:06
I will continue doing this for the remaining scans.
05:09
If I have five scans, I'm going to have
05:12
to match three points five different times
05:15
to get the full registration.
05:20
In the next comparison, I have matched three points,
05:23
and we'll merge the results and see that in this case,
05:26
there was a good match.
05:28
Now I will fast forward to finishing
05:31
with the last of the five scans.
05:33
I will also approve those results.
05:35
And now all of the scans are registered.
05:38
I can look at a quality report to see the entire match status.
05:43
And next, I will move to index the scans.
05:46
This will take a few minutes, so I will fast forward,
05:49
and once the scans are indexed, we will launch the project.
05:53
After launching a project made from structured points,
05:56
we see that there are five orbs, or mirror balls, one
06:01
for each of the scan locations.
06:04
If I select a mirror ball, it changes
06:06
to a panoramic scan view of that location.
06:10
I can spin around, and I can see the photorealistic visual
06:13
quality of that scan.
06:16
I want to use the measurement tool to check
06:18
the size across the pipes.
06:20
This will validate if I'm in the correct units
06:23
and in the correct scale.
06:25
After verifying the measurement, I
06:27
returned to the 3D view and the mirror balls reappear.
06:32
Now I will export this point cloud
06:34
so that I can use it in a variety of Autodesk
06:37
applications.
06:38
I do this from the scan location collection,
06:41
and I want to export this as an RCS file.
06:45
This file will include all the points of the point cloud.
06:49
We could see that there are other point cloud export
06:52
types, such as PTS and E57.
06:56
I will review the unified settings.
06:58
I accept the default value as this scan is not very dense,
07:02
and there is no advantage in decimating
07:05
any closely located points.
07:08
And finally, I select Unify the Project Scan,
07:11
and the output RCS file is created.
07:15
This completes this course objective.
07:18
And now we're ready for the third course objective,
07:21
Using Non-structured Point Cloud Data in Recap.
Try it: Using Structured Data in Recap
