Web and Data Science Center
2012-10-03
Event-based analysis of people’s
activities and behavior using Flickr and
Panoramio geotagged photo collections
Event-based analysis of people’s
activities and behavior using Flickr and
Panoramio geotagged photo
collections
http://bib.dbvis.de/uploadedFiles/264.pdf
Slava Kisilevich, Milos Krstajic, Daniel Keim,
Natalia Andrienko, Gennady Andrienko
University of Konstanz, slaks@dbvis.inf.unikonstanz.de
Fraunhofer Institute IAIS,
gennady.andrienko@iais.fraunhofer.de
Abstract
Photo-sharing websites such as Flickr and Panoramio contain millions
of geotagged images contributed by people from all over the world.
Characteristics of these data pose new challenges in the domain of
spatio-temporal analysis. In this paper, we define several different
tasks related to analysis of attractive places, points of interest and
comparison of behavioral patterns of different user communities on
geotagged photo data. We perform analysis and comparison of
temporal events, rankings of sightseeing places in a city, and study
mobility of people using geotagged photos. We take a systematic
approach to accomplish these tasks by applying scalable
computational techniques, using statistical and data mining algorithms,
combined with interactive geo-visualization. We provide exploratory
visual analysis environment, which allows the analyst to detect spatial
and temporal patterns and extract additional knowledge from large
geotagged photo collections. We demonstrate our approach by
applying the methodsto several regions in the world
Keywords—Geo visual analytics, geotagged images, spatiotemporal
analysis, movement data, clustering
Intro
• Photo-sharing sites Flickr and Panoramio have
billions of photos, publicly available, and
annotated with metadata
– Image size
– Tags
– Titles
– Time Stamps
– Geo Tags
Panoramio Example
What’s Interesting to Us?
• User’s trajectory of sequence of photos
(one user, photos close in time and space)
• Which places are interesting to users
(clusters of photos by geotags)
• Events that are interesting to users
(specific time interval and location range)
• Result: We care a lot about timestamps as well
as geotags.
Related Work
• 2008 – Flickr was
used to identify
regions of high
tourist
concentrations in
Rome
Photo is Figure 1
from the paper
Attractiveness by Density Maps
• The common and fast way to analysis of
attractiveness or activity is to split a
geographical region into cells, count the hits in
each cell, color code the region by the count
http://googlemapsmania.blogspot.com/2012/03/african-conflicts-on-google-maps.html
Related Work
• 2009 – Mean-shift, a non-parametric
clustering algorithm used to find the most
attractive places on Earth via Flickr
http://mobblog.cs.ucl.ac.uk/
30 most photographed
places in Boston
Convex Hulls
• Density based clustering algorithms are a
good way to find attractive areas.
• Density connectivity
between points
using distance and
density thresholds
finds clusters of
photos
Analytical Framework
• Formal Model
O  S  T  A 1  A2    An
where O is the set of objects,
S is the set of places,
T is the set of moments,
and A1, A2,, An are additional attributes of the
events
• A visual representation of the data is needed to
get real value from this model
• Google Earth is a good tool.
• Use brushing, linking, focusing to gain inferences
Data Collection
• Flickr API
– REST (REpresentational State Transfer)
– http://www.flickr.com/services/api/
flickr.photos.search.html
– Many parameters can be used to narrow the
search
– If you don’t narrow the search, Flickr will do it
without telling you
– You can only get 4000 results from any
flickr.photos.search query
Flickr
• To get all Flickr photo metadata, you can ask
how many photos in a region of the earth,
subdivide it and/or time-split it until you get
queries that result in less than 4000 photos
• Alternate approach: Flickr has groups: given a
user id, you can find others with similar
interests and see what they uploaded.
Flickr Search
Flickr Search by Bounding Box
• URL: http://api.flickr.com/servi
ces/rest/?method=flickr.photos.
search&api_key=36aa30d4f02fc667
22ab71cbfb40e2a8&bbox=-180%2C90%2C180%2C90&format=rest
• Or:
&format=json&nojsoncallback=1
JSON (JavaScript Object Notation)
Time-delimited Search of Flickr
URL: http://api.flickr.com/services/rest/?method=flickr.photos.se
arch&api_key=36aa30d4f02fc66722ab71cbfb40e2a8&max_take
n_date=2012-07-07+00%3A00%3A00&bbox=-180%2C-90%2C18%2C90&format=rest
Time-delimited Search of Flickr
URL: http://api.flickr.com/services/rest/?method=flickr.photos.se
arch&api_key=f3794ef16c22e0e96f587fc2a190170e&min_taken
_date=2012-07-07+00%3A00%3A00&bbox=-180%2C-90%2C18%2C90&format=rest
Only those photos from last 12 hours
Panoramio
Panoramio REST
User IDs run from 1 to …
Panoramio by User ID
User ID
•
•
http://www.panoramio.com/map/get_panoramas.php?set=7000000&from=0&to=
10&minx=-180&miny=-90&maxx=180&maxy=90&size=mini_square
{"count":2,"has_more":false,"map_location":{"lat":0.39113999999999999,"lon":36.095782,"panoramio_zoom":0},"photos":[{"height
":32,"latitude":0.39113999999999999,"longitude":36.095782,"owner_id":700000
0,"owner_name":"tincin","owner_url":"http://www.panoramio.com/user/700000
0","photo_file_url":"http://mw2.google.com/mwpanoramio/photos/mini_square/
74216564.jpg","photo_id":74216564,"photo_title":"LakeNakuru","photo_url":"htt
p://www.panoramio.com/photo/74216564","place_id":"9d45290864bf443d6d611
2685668899c315d4050","upload_date":"22 June
2012","width":32},{"height":32,"latitude":0.39113999999999999,"longitude":36.0
95782,"owner_id":7000000,"owner_name":"tincin","owner_url":"http://www.pan
oramio.com/user/7000000","photo_file_url":"http://mw2.google.com/mwpanora
mio/photos/mini_square/74216747.jpg","photo_id":74216747,"photo_title":"Fle
mingo in Lake
Nakuru","photo_url":"http://www.panoramio.com/photo/74216747","place_id":"
9d45290864bf443d6d6112685668899c315d4050","upload_date":"22 June
2012","width":32}]}
Limits
• Panoramio allows 100,000 queries per day
• Any more, and your API ID gets revoked.
• If you want all the meta data from Panoramio,
keep track of the number of queries in the last
24 hours, throttle your app.
Panoramio Results