DroneArt Helsinki

Blog posts:

Wikimaps: http://wikimaps.wikimedia.fi/2015/06/06/julkinen-taide-kaduilta-nettiin/

Wikimedia Finland (en): http://wikimedia.fi/2015/06/06/julkinen-taide-kaduilta-nettiin/

AvoinGLAM: http://avoinglam.fi/?tag=droneart


Which artwork(s) would you like to capture? (And why)

The ones we captured

Kotkia (1913) Yliopiston kasvitieteellinen puutarha Kluuvi Bertel Nilsson (1887–1939). Tiedot Helsingin taidemuseon veistostietokannassa

Convolvulus (1931) Kaisaniemen puisto Viktor Jansson (1886–1958)

Helsingin taidemuseon tietosivu

What equipment could be used, what can you bring?


10.00–11.30 Presentations, lightning talks à 5 min + coffee, making teams 

  • Pitches
  • Maptime! & Wikidays Susanna Ånäs

    CultureJam Sanna Marttila

    Open Finland Challenge "Media, Arts & Culture" Challenge Teemu Ropponen

  • Presentations
  • Wiki Loves Public Art and Public Art Database John Andersson, André Costa

    Wiki Loves Monuments & Mapillary André Costa

    Droning in Sweden (WMSE project page) Jan Ainali

  • About technologies in the process
  • How to get geodata and add it to OSM. Using Field Papers. Pekka Sarkola

    Writing public art to Wikipedia Heikki Kastemaa

    Brief introduction to Wikimedia Commons André Costa

    Brief introduction to Wikidata Jan Ainali (slides used)

    How to capture good image set for 3D-modelling  + Software for 3D imaging VisualSFM, 123D Catch Anssi Krooks <Anssi will arrive on afternoon>

    Requirements of 3D printing Sanna Marttila / Laura Sillanpää

    Overview of different ways of photographing: Cameras, drones, balloons, poles

    12–14 Outdoors capturing data, images

    Possible tasks or teams 

    14–17 Making the 3D models

    Software to download and install

    3DF Lapyx: http://www.3dflow.net/technology/3df-lapyx-camera-calibration-made-simple/

    VisualSFM: http://ccwu.me/vsfm/

    SURE: http://www.ifp.uni-stuttgart.de/publications/software/sure/index.en.html

    Meshlab: http://meshlab.sourceforge.net/

    CloudCompare: http://www.danielgm.net/cc/

    123D Catch http://www.123dapp.com/catch

    FreeFlight 3


    FieldPapers (account)

    What we can do

    Take pictures of the works

    Wikipedia / Wikimedia Commons


    Make 3D models from the images

    Print 3D prints

    Guidelines for photoshoots

    About equipment


  • Camera / mobile phone and a monopod or a stick
  • Drones with in-built cameras
  • This is what we have. http://www.parrot.com/products/bebop-drone/ Each battery last for about 10 minutes, there are 2 of them. 1 hour to charge, so optimally 4 rounds of shooting.

    Some other drones




  • Drone and an additional camera
  • Stillikameran kiinnittäminen phantomiin on myös mahdollista:


  • iPad + 3D scanner
  • abt 500€


  • Helium balloons / kites + a camera
  • Nokia-kamerapuhelimen kiinnitys vaikka helium-palloihin voisi myös toimia.

    Balloon & kite mapping http://publiclab.org/wiki/balloon-mapping

  • Photographing tips
  • http://www.tested.com/art/makers/460142-art-photogrammetry-how-take-your-photos/

    Creating the 3D model

    Photogrammetry • Fotogrammetria

    Easy consumer services

    3d-mallin tekeminen kuvista onnistuu helposti Autodeskin 123d Catch -ohjelmalla puhelimessa tai PC:llä. Muitakin kaupallisia työkaluja on.


    3D mapping program for drones https://pix4d.com/

    Commercial stand-alone program for desktop http://www.agisoft.com/

    The Open Source way 

    VisualSFM is good enough software to produce pointclouds from regular images: http://ccwu.me/vsfm/



    The following is copied from http://wedidstuff.heavyimage.com/index.php/2013/07/12/open-source-photogrammetry-workflow/ and enriched with additions:

    Part 0: Camera calibration (optional)

    Capture series of images of printed checker board (or checker board on computer screen) and use f.ex 3DF Lapyx to calculate camera calibration parameters which will help the next phase

    Part 1: VisualSFM

    VisualSFM lets us load up a folder of images, find unique features in each image, solve a set of these images into a 3D model, and then refine that model into a dense point cloud. The two outputs of this step are:

    If you want to see a video of this process, check this out.

    Part 1.5: Dense matching with SURE

    With SURE you can calculate dense point cloud using the images and orientation files from VisualSFM. In general one 3D point for each overlapping image pixel is generated -> very detailed point cloud as a result

    Part 2: Meshlab

    Meshlab allows us to do basically anything to a 3D mesh or a point cloud. We’ll take the two outputs from the above steps and produce a textured, clean, high-res mesh. Meshlab also automatically calculates UV maps (the basis for 3D texturing) and builds a texture for us by estimating which projector is most accurate on each spot of the model, which is insanely cool. The outputs of this step are:

    Täällä jonkinlainen kirjasto drone-kuvaamiseen:


    Displaying point clounds on the web

    Vaihtoehtoisesti, patsaasta ja sen ympäristöstä voi tehdä point cloudin ja laittaa sen Potreetä käyttämällä esimerkiksi verkkoon:


    Creating panoramas

    Olen tehnyt Huginilla joitakin kokeiluja siitä, miten dronen videokuvasta saisi panoraaman tehtyä. Laatu ei dronen omalla kameralla ole ollut kovin häävi, skriptejä on täällä:




    Interesting links

    Public art


    Participatory mapping