It is very rare for me to read about photography on blogs that have to do with computer science and programming, but this week I came across a very interesting study that combines computer science and picture organization methods. The study was done by Cornell University faculty and students and was presented at the 2009 edition of the International World Wide Web conference. It was entitled “Mapping the world’s photos” (See resources at the end for the PDF link).

What is this about?

While it was not a simple read, it was definitely very captivating …I know I’m weird because I like reading research papers. Well, here is the abstract of the paper to give you an idea what it is about.

“We investigate how to organize a large collection of geotagged photos, working with a dataset of about 35 million images collected from Flickr. Our approach combines content analysis based on text tags and image data with structural analysis based on geospatial data. We use the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places. We then study the interplay between this structure and the content, using classification methods for predicting such locations from visual, textual and temporal features of the photos. We find that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features. We illustrate using these techniques to organize a large photo collection, while also revealing various interesting properties about popular cities and landmarks at a global scale.”

35 million pictures ?! That’s a lot of pictures…a lot more than what any of us would have to ever deal with on our own computers at home.

What does this mean?

While I can’t claim that I have studied the paper in depth or that I understand all its implications, I believe that I can summarize a few things. Here’s my take on some aspects of this paper. We all know how to tag our images, and how to add image geotags. We have also learned that our cameras add EXIF image metadata that contains the date and time when each picture was taken. So, what happens when you put all this information together? Well, initially you get a large amount of data and that’s about it! But what happens if you divide all these pictures and data by individual photographers? This is when things start to get interesting…actually very interesting. If one is able to map all the pictures of one photographer taken at a particular tourist attraction and combine that with the time when each picture was taken, you can essentially follow that photographer as he or she was taking pictures. Now, throw in the mix a very large number of pictures…about 35 million pictures from Flickr. Then you can create maps of cities with popular landmarks. Not only that but these maps are also showing the route tourists take when visiting the city. You also start getting a really good sense about what landmark is popular and what the relationship between a landmark and any other spot around that landmark is.

Next Page:The coolest statistics

Pages: 1 2

1. How to use your image geotags in Flickr
2. 2 simple examples of using image geotags
3. Image metadata terms definition
4. The best history lesson on image metadata standards
5. Understand and manage your image metadata

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