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  • Imagine: make a trip and take some pictures.

  • Upload them on the web, and get this:

  • At the bottom there are the stages of your trip: let's begin with Santiago of Chile.

  • At the center you can see your pictures that are possible to scroll with the forward and back buttons.

  • Scrolling the picture, at the right, your trip will be reconstructed on a map:

  • actually, the position will be indicated for every picture that has been taken.

  • On the left side, a tagcloud will be created in relation to the pictures that you see.

  • Continuing with your trip, you can scroll the stage always keeping

  • visible your way and the tagcloud associated to the picture.

  • You can also skip some stages by choosing oneyou are interested in.

  • Let's go to San Pedro.

  • Unfortunately, your camera broke and you bought a new one provided with an integrated compass:

  • now the map is able to indicate, besides the position of the picture,

  • the direction towards the picture was taken.

  • The first picture was taken towards north;

  • the second one was taken towards east, and so on and so forth.

  • The system should be able to organize your pictures without your involvement.

  • However, you can edit the map-position and customize the tagcloud.

  • Let's begin with the position of the first picture, taken in Santiago of Chile.

  • After having pressed the edit button, it will be possible to edit the position of the marker doing drag&drop.

  • Alternatively, clicking on the marker, it will be possible to associate a new address or new geographic coordinates.

  • The same process will be possible for tags: if you are not satisfied with automatic tags

  • associated to the picture, you can remove some of them.

  • You can increase the ranking of the tag.

  • You can decrease the ranking of another one.

  • Finally, you can add your own tags!

  • Every change you make will contribute to improve the automatic identification of the best tags for every picture.

  • The system is smart, and able to learn!

  • This is likely a better proposal of design.

  • Both of them are representations of the general idea of this project.

  • However, the interface will be definitely designed through more accurate studies.

  • Every camera recently produced is able to date and geotag every picture.

  • Every picture is inserted in a space-temporal context.

  • This information is saved through adequate metadata in every jpeg picture.

  • Uploading a set of pictures, the system is able to cover the space-temporal context of your trip.

  • ...or of your life!

  • During your trip, you take many pictures.

  • During your trip, you also move around a place, continuing to take pictures.

  • The algorithm is able to cluster these pictures considering two criteria:

  • the geographic proximity

  • and the temporal proximity.

  • Every identified group is a stage of your trip.

  • Every customization of tag-clouds associated to every picture

  • contributes to teach the system what the most used tags are for every geographic position.

  • For instance, if people take some pictures in the proximities of the Colosseum, in Rome,

  • the most common word to tag these pictures will be "Colosseum".

  • The system, in this way, is able to learn that in the proximities of these geographic coordinates,

  • the tag "Colosseum" is very used, becoming statistically relevant.

  • In this way every time that there is a picture in the proximities of these geographic coordinates,

  • the system will assign automatically the tag "Colosseum"

  • ...and those that are statistically relevant!

Imagine: make a trip and take some pictures.

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