A Neil for Sunday

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Extracts from an Audience with Neil Gaiman can be found in PODCASTS.

 

    Project Tango

    A mobile phone equipped with a 3D imaging sensor has finally arrived. The fact that is has been developed by Google makes it a technology worth keeping an eye on. Given the experience Google has with mapping enviroments, which includes working with laser scanning companies like Velodyne, Tango is well placed to drive forward the idea of affordable 3D. It is not just a case of watch this space but wait to see how it is documented too.

    Prior to the acquisition of Prime Sense by Apple in November 2013, the Capri sensor looked like a viable way to turn mobile devices into 3D documentation tools.

    ETH Zurich, who appear to be a partner on Project Tango,  also came up with their own SfM based solution on a standard Andriod phone.

     

     

     

     

     

     

     

     

     

     

     

      Disaster Management Imaging

      Digital terrain modelling “DTM” will play an increased role in how disasters are managed in the future. The foundations for this were set in the first quarter of 2014 through the media coverage for weather conditions in the USA and UK. There were enough free services and solutions in general circulation – be it open source Geographical Information Systems “GIS” or camera based mapping – for  risk management strategies to be considered before the snow and rain set in. Even an image search in Google could have been used to generate 3D data for highly documented areas.

      3D Mapping

      The most obvious choice in terms of 3D mapping is structure-from-motion “SfM” – a low cost methodology that uses a flexible camera model to reconstruct a scene.  The SFM Toolkit / VisualSFM can be used to generate a point cloud from a desktop computer, with Meshlab used to convert it into a solid surface mesh. Once this is achieved, the next logical option is scaling the data to absolute coordinates in GIS. While data of a lower resolution may not be ideal for object or structure documentation, its use in landscape mapping is ideal if the accuracy required is in meters or even kilometers.