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MIS @ Retrieving
Diverse Social Images Task 2015
Lukas Diem and Maia Zaharieva
MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
Features
• Visual-based
• CNN adapted features provided by the organizers
• Text-based
• LDA (Latent Dirichlet allocation)
• Title and tags
• 50 topics per query
• TF-IDF
• Title, tags, and description
• Cleanup step and handling of missing text
Approach
• Data preprocessing
• Face and GPS filter
• Relevance reranking
• Visual-based similarity to wiki or top 10 images
• CNN outperforms other features significantly
+15% P@20 compared to CN3x3
• Image clustering and selection
• AHC with Ward’s aggregation and 50 clusters
• Round-Robin selection approach
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
LDA
TF-IDF
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
LDA
TF-IDF
CNN
Lessons Learned
Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
LDA
TF-IDF
CNN
LDA
TF-IDF
Thank you
Contact: Lukas Diem, l.diem@univie.ac.at
MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany

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MediaEval 2015 - MIS @ Retrieving Diverse Social Images Task 2015

  • 1. MIS @ Retrieving Diverse Social Images Task 2015 Lukas Diem and Maia Zaharieva MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
  • 2. Features • Visual-based • CNN adapted features provided by the organizers • Text-based • LDA (Latent Dirichlet allocation) • Title and tags • 50 topics per query • TF-IDF • Title, tags, and description • Cleanup step and handling of missing text
  • 3. Approach • Data preprocessing • Face and GPS filter • Relevance reranking • Visual-based similarity to wiki or top 10 images • CNN outperforms other features significantly +15% P@20 compared to CN3x3 • Image clustering and selection • AHC with Ward’s aggregation and 50 clusters • Round-Robin selection approach
  • 4. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
  • 5. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
  • 6. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany
  • 7. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany LDA TF-IDF
  • 8. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany LDA TF-IDF CNN
  • 9. Lessons Learned Lukas Diem, MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany LDA TF-IDF CNN LDA TF-IDF
  • 10. Thank you Contact: Lukas Diem, l.diem@univie.ac.at MediaEval 2015 Benchmark Workshop, September 14-15, Wurzen, Germany