Exploiting User Generated Content for Mountain Peak Detection

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CUbRIK research used for the classification of mountain panoramas from user-generated photographs followed by identification and extraction of mountain peaks from those panoramas.

Technology Education

1/05/2013
SoHuman 2013 at
ACM Web Science 2013 1
Exploiting User Generated Content for
Mountain Peak Detection
Roman Fedrov, Davide Martinenghi,
Marco Tagliasacchi, Andrea Castelletti

2
Passive Human Computation
User Effort
SoHuman 2013 at
ACM Web Science 20131/05/2013

3
Passive Human Computation
Collective Intelligence
SoHuman 2013 at
ACM Web Science 20131/05/2013
Our Goal
Retrieve the collections of the mountain
appearances in different time instants and build
environmental models.
201320122011201020092008
Key Problem
Identify the mountains

4
Key Problem: Object Identification
Input
SoHuman 2013 at
ACM Web Science 20131/05/2013
46° 0’ 48.51” N
7° 48’ 6.62” E
http://www.udeuschle.de/Panoramen.html

5
Key Problem: Object Identification
Output
SoHuman 2013 at
ACM Web Science 20131/05/2013

6
Matching Algorithm
SoHuman 2013 at
ACM Web Science 20131/05/2013
Steps
Scale
Render
Extract Edges
Filter
Match

7
Matching Algorithm
SoHuman 2013 at
ACM Web Science 20131/05/2013
Steps
Scale
Render
Extract Edges
Filter
Match

8
Matching Algorithm
SoHuman 2013 at
ACM Web Science 20131/05/2013
Steps
Scale
Render
Extract Edges
Filter
Match

9
Matching Algorithm
SoHuman 2013 at
ACM Web Science 20131/05/2013
Steps
Scale
Render
Extract Edges
Filter
Match

10
Matching Algorithm
SoHuman 2013 at
ACM Web Science 20131/05/2013
Steps
Scale
Render
Extract Edges
Filter
Match
Adapted from matching technique by Baboud et al. “Automatic photo-to-terrain alignment for
the annotation of mountain pictures”, CVPR 2011

11
Results
SoHuman 2013 at
ACM Web Science 20131/05/2013
 62% of correct match as maximum result
 81% of correct match in top-10 positions

12
Potential Applications
SoHuman 2013 at
ACM Web Science 20131/05/2013
http://www.nohrsc.noaa.gov/
Augmented Reality
Environmental Models
Colle dei BreuilFurgggrat

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Exploiting User Generated Content for Mountain Peak Detection

1. 1/05/2013 SoHuman 2013 at ACM Web Science 2013 1 Exploiting User Generated Content for Mountain Peak Detection Roman Fedrov, Davide Martinenghi, Marco Tagliasacchi, Andrea Castelletti

2. 2 Passive Human Computation User Effort SoHuman 2013 at ACM Web Science 20131/05/2013

3. 3 Passive Human Computation Collective Intelligence SoHuman 2013 at ACM Web Science 20131/05/2013 Our Goal Retrieve the collections of the mountain appearances in different time instants and build environmental models. 201320122011201020092008 Key Problem Identify the mountains

4. 4 Key Problem: Object Identification Input SoHuman 2013 at ACM Web Science 20131/05/2013 46° 0’ 48.51” N 7° 48’ 6.62” E http://www.udeuschle.de/Panoramen.html

5. 5 Key Problem: Object Identification Output SoHuman 2013 at ACM Web Science 20131/05/2013

6. 6 Matching Algorithm SoHuman 2013 at ACM Web Science 20131/05/2013 Steps Scale Render Extract Edges Filter Match

7. 7 Matching Algorithm SoHuman 2013 at ACM Web Science 20131/05/2013 Steps Scale Render Extract Edges Filter Match

8. 8 Matching Algorithm SoHuman 2013 at ACM Web Science 20131/05/2013 Steps Scale Render Extract Edges Filter Match

9. 9 Matching Algorithm SoHuman 2013 at ACM Web Science 20131/05/2013 Steps Scale Render Extract Edges Filter Match

10. 10 Matching Algorithm SoHuman 2013 at ACM Web Science 20131/05/2013 Steps Scale Render Extract Edges Filter Match Adapted from matching technique by Baboud et al. “Automatic photo-to-terrain alignment for the annotation of mountain pictures”, CVPR 2011

11. 11 Results SoHuman 2013 at ACM Web Science 20131/05/2013  62% of correct match as maximum result  81% of correct match in top-10 positions

12. 12 Potential Applications SoHuman 2013 at ACM Web Science 20131/05/2013 http://www.nohrsc.noaa.gov/ Augmented Reality Environmental Models Colle dei BreuilFurgggrat

Exploiting User Generated Content for Mountain Peak Detection

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