Arc-Team tries Large Scale Reflectance Transformation Imaging (RTI)

With the data, collected during our mission presented recently in the post „@MAP“the Arc-Team Mobile Mapping Platform, we've tried for the first time to apply a method called Reflectance Transformation Imaging (RTI) on landscape:

Aerial Photo of the project area taken from Arc-Teams Drone

„RTI is a computational photographic method that captures a subject’s surface shape and color and enables the interactive re-lighting of the subject from any direction. RTI also permits the mathematical enhancement of the subject’s surface shape and color attributes. The enhancement functions of RTI reveal surface information that is not disclosed under direct empirical examination of the physical object. (...) RTI images are created from information derived from multiple digital photographs of a subject shot from a stationary camera position. In each photograph, light is projected from a different known, or knowable, direction. This process produces a series of images of the same subject with varying highlights and shadows. Lighting information from the images is mathematically synthesized to generate a mathematical model of the surface, enabling a user to re-light the RTI image interactively and examine its surface on a screen.“ (http://culturalheritageimaging.org/Technologies/RTI/)

We've used the processing software and viewer of Cultural Heritage Imaging, their RTIBuilder software is made available under the Gnu General Public License ver. 3.

http://culturalheritageimaging.org/IMAGES/lintel_specular_split_detail.jpg

RTI is usually used for objects of small or medium size beause of the difficulty or impossibility to illuminate whole structures or even areas / landscapes.

At this point GIS comes to our aid:

Starting from a DTM it's easily possible to create shadow reliefs with GRASSGIS' module r.shaded.relief. 

The highlight of the module in our case is the capability to modify the altitude of the sun in degrees above the horizon and the azimuth of the sun in degrees to the east of north. 

In this way we could produce artificially the needed data for our RTI-landscape attempt. 

The next step was to export from GRASS a set of 60 images with different lighting positions creating an imaginary light dome around the object:

At this point we reached the first bottelneck of our approach:

Usually, you include at least one reflective sphere in each shot. 

The reflection of the light source on the spheres enables the processing software to calculate the light direction for that image. 

So we had to create and copy in every image a fake sphere with the reflection corresponding to the sunlight direction choosen in GRASS.

It was a stiff piece of work!

At the end everything was ready for processing the images in RTIBuilder. The single steps in the software are very easy to execute and well described on the ProcessingGuide. 

We've just had some problems with the size of our images (8200x6500 pixels), which the software couldn't process, but maybe it was because of the age of our hardware...

After reducing the image-size everthing worked fine...

At the end, after installing also RTIViewer, we've held in our hands an interactive scene of an archaeological site of nearly 10.000m² which is almost invisible from the ground.

„@MAP“ the Arc-Team Mobile Mapping Platform

In Summer 2013 Arc-Team was charged with the task to survey a micro-DTM on an archaeological area of about 10.000 m2.

The underlying archaeological remains on the side cause small differences in height on the surface and the shape of a nearly 60 x 60 meters large structure was known from aerial photographs.

We've had only 10 hours of fieldwork at our disposal and exploring our options we've made some numbers games:

• Doing the job with total station would allow us to take an average of 5 points per minute, which means a (very optimistic) total amount of 3000 points in 10 hours. (2 operators)

• Using our DGPS, the stroke per minute increases up to a maximum of 15 points per minute, working with continuous point capturing mode, having an operator on the field who's stepping forward, putting down the pole and balancing the bubble eyery 4 seconds. The total amount in this case is about 9000 points. This means an average of only 0,9 points / m2. That would be far to few...

So what would we going to do?

In this occasion we've had the idea to adapt a monocycle in order to have a rollable vehicle carrying the GPS antenna and maintaining a constant distance to the ground.

The result you can admire in the illustration below.

By the help of this tool we were able to increase the stroke on 42 points / minute and a total amount of almost 25.000 points. This means an average of at least 2,5 points / m2.

The result of our efforts was quite lovely: GRASS GIS produced a high quality DTM from which we derive 3D views, isolines and shaded reliefs.

The official name of the trolley is „@MAP“ Arc-Team Mobile Mapping Platform. ;-)

Cloud distance tool.

I was working on different SfM/IBM of a grave we dug in 2010. we have the documentation of four different levels (see picture below). It was a complex archaeological context, with two skeletons buried in different times (double burial), both partially destroyed by the construction of the Renaissance apse. Moreover the tomb was built on the side of a prehistoric house.

I tried to rectify the point clouds inside CloudCompare v. 2.4 (normally i use GRASS with the ply importer addon or MehLab) and I discover this fantastic tool: compute cloud/cloud distance. It can calculate the distance between two different overlapping mesh, similarly to the GRASS command "r.mapcalc". As you can see in the pictures below, the distance analysis between the first and the last documentation can represent the quantity of removed ground. It could be really useful for analysis of damages in buildings.

first point cloud

fourth point cloud

cloud/cloud distance

cloud/cloud distance over the fourth point cloud

Voxel for archaeology

This video regards a pretty old experiment we did in 2006 to understand the possibility of volumetric graphic (voxel) in archaeology. The data came from my thesis (University of Padua, professor G. Leonardi) and were elaborated inside GRASS. The 3d surfaces of top and bottom interfaces of one layer were imported into the GIS to produce a volumetric representation. This was possible thanks to the effort of Soeren Gebbert, who wrote a script to export the voxel from GRASS into a VTK file (which we loaded in ParaView). At the and of the experiment we had a complete virtual representation of the archaeological record (a destroyed burial connected with incineration practices). This "digital copy" was composed by two 3d raster surfaces (top and bottom), one volumetric reconstruction of the layer (voxel) and a lot of 3d vector levels of the finds (fragment of burned human bones, pottery and bronze). Below you can see a picture of the situation before a started to dig.