PS-09
A Context-Aware Late-Fusion
Approach for Disaster Image
Retrieval from Social Media
Minh-Son Dao1,2, Pham Quang Nhat Minh3,
Asem Kasem1
1 Universiti Teknologi Brunei
2 NICT, Japan
3 Alt Vietnam Co., Ltd, Vietnam
ICMR 2018
June 11-14, 2018, Yokohama, Ja
Challenges and Motivation
No-Flood
Flood
Flood Images Retrieval from Social Media
Non synchronization between the
content of an image and metadata from
the same post
Flood?
Flood?
The similarity of texture, colour, and spatial relation of different regions
between non-flood and flood images
ICMR 2018
June 11-14, 2018, Yokohama, Ja
Using Visual Features Only
Re-ranking
Collecting data
near by the
hyperplane of
the first classifier,
then training
them with the
second classifier
with other
features
Utilize a fixed number of visual features with a proper fusion scheme to
MFC: multimodal features combination, SL:retrieve
supervised images
learners , F: feature, MDS: multiple data set , PR:
prediction
ICMR 2018
June 11-14, 2018, Yokohama, Ja
Using Metadata Features Only
Simple Feed-Forward Neural Network
ICMR 2018
June 11-14, 2018, Yokohama, Ja
Using Visual, Metadata, and
External Resources
ICMR 2018
June 11-14, 2018, Yokohama, Ja
Only Using Visual Features provided by the organizer
Experimental Results
Run 1: Visual Only, Run 2: Metadata Only, Run 3: Visual + Metadata
Run 4: Visual, Metadata, and External data
ICMR 2018
June 11-14, 2018, Yokohama, Ja
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ICMR 2018
June 11-14, 2018, Yokohama, Ja