1. Minh S. Dao, Truc-Vien Nguyen, Giulia
Boato, Francesco G.B. De Natale
University of Trento, Italy
@MediaEval 2012-SED task

2. Watershed transform Social Event Detection
Idea:
- People tend to introduce similar
annotations for all images associated to
the same event -> homogeneous
regions
- People cannot be involved in more than
one event at the same time -> borders
among events, stop condition
http://cmm.ensmp.fr/~beucher/wtshed.html
Target: Target:
- Markers and all pixels sharing the - Events and all images associated
same characteristic (segmented with these events
homogeneous regions)
Need: Image that needs to be segmented, Markers, Flood progress (stop-condition)

3. time (col)
... ...
username = «procsilas»
dateTaken = «2009-01-17»
username = «procsilas»
dateTaken = «2009-01-17» ...
... ...
... ... ...
username = «sarahamina» username = «sarahamina» username = «sarahamina»
dateTaken = «2009-01-13» dateTaken = «2009-01-13» ... dateTaken = «2009-01-12»
... ... ...
... ...
username = «Xaf»
dateTaken = «2009-01-10»
username = «Xaf»
dateTaken = «2009-01-10»
...
... ...
. . . .
. . . .
users(row)
. . . .
... ... ...
username = «sarahamina» username = ... username = ...
dateTaken = «2009-01-12» dateTaken = ... dateTaken = ...
... ... ...

4. photo_url
username
dateTaken
title
description
tags
locations
UT image

5. Watershed transform
Hint 1: left- and right- neighbor pixels: http://cmm.ensmp.fr/~beucher/wtshed.html
can be flooded from markers
Hint 2: one segment of one
Why?
user can be merged to another
- People tend to introduce similar
segment of another user as
annotations for all images associated
long as they share the same
to the same event.
MARKERs
- People cannot be involved in more
than one event at the same time

6. www.oxforddicti
onaries.com
www.macmillan Tf-idf (keywords
dictionary.com + semantic
relatedness)
Tf-idf (locations
+ geodistance)
- Synonym
- Semantic (keywords,
relatedness locations)
- Fixed terms
Geodistance
www.froscon.de
www.cebit.de
-----------------
www.allconferences.com Wiki
index.conferencesite.eu – list of cities of a country
www.tradeshowalert.com - List of public place of a
----------------- city
www.ieee.org http://www.infoplease.co
www.acm.org m/ipa/A0001769.html
(cities and GPS)

7. Step 1: (time direction)
- left- and right- neighbor
pixels: be flooded from
markers with mergin-
condition(time, tags, [locatio
n])
- Markers also can be merged if
they satisfy merging-
condition
Step 2: (user direction)
- Each chunk of each marker of
one user will be merged with
UT image other chunks of another users

8. Discussion
- Fixed terms (i.e. technical events that for sure are
organized only in Germany, for example CeBIT, FrosCon)
can improve Precision
- Semantic Relatedness could help to get rid of or
decrease influences of «irrelevant» or «low sematic
relatedness relevant»
- Merging-condition should be improved to increase Recall
- Geodistance sphere should be defined for each
city/public places
- Roles of external data sources are important to prune
(keywords, location) markers.
- Only English (semantic relatedness, keywords, cities
names)

9. - Visual information
- Individual Geodistance sphere
- Merging-condition w.r.t features’
influences
- Various threshold for tf-idf
- More languages (now only
English)