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Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

dilpreet.co

31–40 of 77 posts

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#31
post #25

I don't get it why ML is needed. Just download a DEM (for example, an aerial LIDAR map or SRTM), import it in QGIS along with your base map raster, choose the appropriate shading parameters and combine the two with appropriate blending. edit: and if you're feeling fancy, you can render the relief shading in blender: https://somethingaboutmaps.wordpress.com/2017/11/16/creating...

> Many standard shading algorithms exist for creating shaded reliefs, some can easily be found in applications like ArcGIS and QGIS but they are simply not expressive enough (see our paper for examples). Creating these reliefs is partially an art form rather than a simple illumination problem, so trying to encode the 'human-ness' into step-by-step algorithms is simply too difficult. This is where ML enters the pictur…

> an art form

Which is why the linked Daniel Huffman's technique employed the convincing results of Blender.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#32
post #23

Earlier quoted context omitted.

But if you try using the factually correct angle (light from some angle in the south), the result is misleading to the eye.

Sometimes, but not always: it likely depends on the style of the map and how accurate it is as well I think, and maybe depends on people's perception: thanks to computer UI buttons from the 90s, it is common for upper and left-most surfaces/bevels to be lighter, so there is some assumption there. i.e. I think this type of thing: https://cartographart.com/minimalist/iceland_2_5k_orth_occlu... works well, but that's no…

> depends

In fact it works with the provided example but, empirically, it does not on area detail of detailed maps. Crests and valleys will switch.

> computer UI buttons

That is a consequence of consolidated established style, not a cause.

> the whole of Africa

It will work on the view of the full shape but it will not on the area detail, where the viewer will lose the notion of global position and attempt to interpret it like any other spot.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#33
post #31

Earlier quoted context omitted.

> Many standard shading algorithms exist for creating shaded reliefs, some can easily be found in applications like ArcGIS and QGIS but they are simply not expressive enough (see our paper for examples). Creating these reliefs is partially an art form rather than a simple illumination problem, so trying to encode the 'human-ness' into step-by-step algorithms is simply too difficult. This is where ML enters the pictur…

> an art form Which is why the linked Daniel Huffman's technique employed the convincing results of Blender.

The biggest thing that I'm seeing that Singh has over Huffman is the adjustable detail-preserving terrain smoothing. Detail-preserving blur algorithms don't generalize well. Application-specific NN solutions tend to excel at this problem, by having a model of what details are important vs incidental.

I would like to see a combination of the two, with the terrain pre-processed before being used in Blender.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#34
post #25

I don't get it why ML is needed. Just download a DEM (for example, an aerial LIDAR map or SRTM), import it in QGIS along with your base map raster, choose the appropriate shading parameters and combine the two with appropriate blending. edit: and if you're feeling fancy, you can render the relief shading in blender: https://somethingaboutmaps.wordpress.com/2017/11/16/creating...

I was wondering about that too. The direction of a high quality shading is not uniform: https://i.imgur.com/Y8hIWAD.png (taken from Fig. 3 in the paper)

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#36
post #31

Earlier quoted context omitted.

> an art form Which is why the linked Daniel Huffman's technique employed the convincing results of Blender.

The biggest thing that I'm seeing that Singh has over Huffman is the adjustable detail-preserving terrain smoothing. Detail-preserving blur algorithms don't generalize well. Application-specific NN solutions tend to excel at this problem, by having a model of what details are important vs incidental. I would like to see a combination of the two, with the terrain pre-processed before being used in Blender.

This is a similar problem as automatic LOD computation for 3D game assets though, and that has been done for a long time without ML (but maybe ML may actually help there too, no idea).

I still find the 'human touch' argument a bit unconvincing for this type of problem.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#37
post #32

Earlier quoted context omitted.

Sometimes, but not always: it likely depends on the style of the map and how accurate it is as well I think, and maybe depends on people's perception: thanks to computer UI buttons from the 90s, it is common for upper and left-most surfaces/bevels to be lighter, so there is some assumption there. i.e. I think this type of thing: https://cartographart.com/minimalist/iceland_2_5k_orth_occlu... works well, but that's no…

> depends In fact it works with the provided example but, empirically, it does not on area detail of detailed maps. Crests and valleys will switch. > computer UI buttons That is a consequence of consolidated established style, not a cause. > the whole of Africa It will work on the view of the full shape but it will not on the area detail, where the viewer will lose the notion of global position and attempt to interpr…

> In fact it works with the provided example but, empirically, it does not on area detail of detailed maps. Crests and valleys will switch.

I don't think that's always the case though: I think it's likely similar to optical illusions: you can technically correctly see it both ways, but it depends on the person's brain and what they're used to as to how their brain sees it.

> That is a consequence of consolidated established style, not a cause.

I didn't say it was a cause, I said that it might lead people to be able to more readily recognise top/left as the lighting direction more readily as "raised" due to being used to computer UIs having top/left being lighter signifying raised elements, and them being more familiar with it that way.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#38
post #14

In Swiss-Style Relief shading, the light comes from North West, which is impossible in the northern hemisphere. This makes sunny south facing slopes shaded and shaded north facing slopes light. Legend says that this was an intentional design decision, because right handed people usually have their desk lighting on the top left of their desk, giving the map a 3D like appearance. Here's an article on the topic (german…

> In Swiss-Style Relief shading, the light comes from North West

I would rather say it comes from the top-left. If you orient your map with the south upwards, it will look ok, as if the relief was shaded in the morning.

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#39
post #16

I'm facing the issue on how to aesthetically visualize my hiking and skiing GPS tracks in mountainous terrain (similar to the OP, I live in Switzerland, so it's either up or down). I've decided to go directly the 3D route using Babylon.js, see here for an example: https://cubetrek.com/view/6338 Within Switzerland, it also uses Swiss-style maps as texture, outside of Switzerland a visually similar map style. I'm looki…

Looks fun. I just tried to sign up, but the link I received by email redirected to http://localhost:8080

Re: Eduard: Swiss-Style Relief Shading for Maps Using Machine Learning

#40

Why would you use a black box ML model for such a well-defined rendering task is beyond me...

> The network was able to learn key design principles from manual reliefs such as removing unnecessary terrain details, adjusting illumination direction, and varying brightness to emphasise larger landforms.
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