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UPC at MediaEval Social Event Detection 2013

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Joint work with Daniel Manchon-Vizuete (Pixable)

More details:
https://imatge.upc.edu/web/publications/upc-mediaeval-2013-social-event-detection-task

Published in: Technology, Sports
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UPC at MediaEval Social Event Detection 2013

  1. 1. UPC @ MediaEval 2013 Social Event Detection (Task 1) Daniel Manchón-Vizuete Xavier Giró-i-Nieto Barcelona, Catalonia 19th October 2013
  2. 2. Motivation
  3. 3. Challenge
  4. 4. Challenge
  5. 5. Related work PhotoTOC [Platt et al, PACRIM 2003]
  6. 6. Approach (a) Temporal sorting by each user independently Hi, I’m John. Hi, I’m Emily.
  7. 7. Approach (b) Temporal-based oversegmentation in mini-clusters PhotoTOC [Platt et al, PacRim 2003]
  8. 8. Approach (b) Temporal-based oversegmentation in mini-clusters
  9. 9. Approach (c) Sequential merging of mini-clusters avg(·) avg(·) ? avg(·) avg(·) t
  10. 10. Approach (c) Sequential merging of mini-clusters Weighted modalities ● ● ● ● creation (or upload) time geolocation textual labels same user
  11. 11. Approach (c) Sequential merging of mini-clusters Time stamp (d=L1) Text labels (d=Jaccard) Geolocation (d=haversine) Same user (d=boolean)
  12. 12. Approach (c) Sequential merging of mini-clusters Weighting factors (wi) Time Learned weights GPS Labels User 0.06 0.28 0.22 0.44 0.08 - 0.30 0.60
  13. 13. Approach (c) Sequential merging of mini-clusters Average and deviation learned on pairs of photos within the same training event. z-score
  14. 14. Approach (c) Sequential merging of mini-clusters phi function
  15. 15. Approach (c) Sequential merging of mini-clusters decision threhold
  16. 16. Approach (c) Sequential merging of mini-clusters
  17. 17. Results (required only) F1 NMI Divergence F1 Heuristic weights (*) 0.8798 0.9720 0.8268 Learned weights 0.8833 0.9731 0.8316 (*) wtime=0.2, wgeo=0.2, wtext=0.2, wuser=0.4,
  18. 18. Conclusions ● Fast solution due to time-sequential nature. ● Divide and conquer. ● Little gain with this optimisation approach. ● Intuition: Thresholds should be event-dependent. @DocXavi #mediaeval13 Thank you MediaEval SED !

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