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Loud and Trendy: Crowdsourcing Impressions of Social Ambiance in Popular Indoor Urban Places

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Slides from the talk given at ACM Multimedia 2015 in Brisbane.

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Loud and Trendy: Crowdsourcing Impressions of Social Ambiance in Popular Indoor Urban Places

  1. 1. Loud and Trendy: Crowdsourcing Impressions of Social Ambiance in Popular Indoor Urban Places Darshan Santani, Daniel Gatica-Perez Idiap and EPFL Switzerland 28 October 2015 ACM MM 2015, Brisbane
  2. 2. Which place looks more “romantic”? A B
  3. 3. Which place feels more “loud”? A B
  4. 4. Understanding Social Ambiance of Urban Places Place impressions define our favorite hangouts and shape our new discoveries Social ambiance elicited by perceptual cues and prior knowledge Connections between psychological features of cities and key indicators like well-being and prosperity Our goal: to provide “a better idea of how people perceive and experience places”
  5. 5. Brave New Idea?
  6. 6. Social Media Mobile Technologies Lots of images
  7. 7. Lighting Spatial Layout Flooring Wall Decorations Table Layout Ceiling
  8. 8. Holistic study of place ambiance would involve interpretation of multiple sources of information, including subtle visual (and audio) cues → Many challenges for multimedia research Open Issue: Multimedia approaches to study social perception of urban places.
  9. 9. Research Questions ● RQ1: What types of social media images are perceived as being more informative of the ambiance of popular indoor places? ● RQ2: Can the ambiance of an indoor place be reliably assessed by observers of social media images? If so, for what dimensions of ambiance?
  10. 10. Dataset – Places Singapore NYC Seattle Mexico City Barcelona Paris 50 popular places per city Places: cafes, restaurants, bars, or clubs
  11. 11. Dataset – Places Singapore NYC Seattle Mexico City Barcelona Paris 50 popular places per city Places: cafes, restaurants, bars, or clubs
  12. 12. Dataset – Places Singapore NYC Seattle Mexico City Barcelona Paris 50 popular places per city Places: cafes, restaurants, bars, or clubs
  13. 13. Image Dataset #1 ● Random Image Corpus ● 50,000+ images for all 300 places via 4SQ API ● 55% iPhone; 19% Android; 22% via Instagram ● Randomly selected 3 images per place for a total of 900 images
  14. 14. Image Dataset #2 ● Physical Environment Image Corpus ● Clear views of the environment (manually chosen) ● 3 images per place for a total of 900 images
  15. 15. RQ1: What types of social media images best convey the ambiance of popular indoor places? Use image corpora to judge which image selection approach results in images being perceived as more adequate to convey ambiance.
  16. 16. Methodology ● Crowdsourcing via Mechanical Turk ● 5 images – 2 from the Physical Environment image corpus, and 3 from Random image corpus ● Tasks: ● Rank the images based on how informative they are of the ambiance of a place ● Categorize the images in one of the four classes: – Food/Drinks, – People/Group, – Physical Environment, and – None of these.
  17. 17. Results Images from Phy.Env. corpus are in Top 2 ranks 91.7% for ambiance
  18. 18. Results Images from Phy.Env. corpus are in Top 2 ranks 91.7% for ambiance 96% of Phy. Env. Image corpus describe the physical environment 67% Random image corpus describe either food or people
  19. 19. Results Phy. Env. image corpus describe the physical environment in 96.2% of the cases Random image corpus describe food items or people in 67% of the cases Finding from RQ1: Images with clear views of the environment are perceived as more suitable to characterize indoor ambiance.
  20. 20. RQ2: Can the ambiance of an indoor place be reliably assessed by observers of social media images? If so, for what dimensions of ambiance?
  21. 21. Methodology ● Crowdsourcing via Mechanical Turk ● Data: Phy. Env. Corpus 900 images across 300 places ● Ambiance Labels: 13 dimensions [Graham, 2011] ● Task: Rate personal impressions of the place ambiance along 13 dimensions on a 5-point Likert scale ● 10 annotations for each dimension per place → 3,000 responses. [Graham 2011] L. T. Graham, & S. D. Gosling, “Can the ambiance of a place be determined by the user profiles of the people who visit it?”. In the Fifth International AAAI Conference on Web and Social Media (ICWSM), 2011
  22. 22. Artsy Bohemian Conservative Creepy Dingy Formal Sophisticated Loud Old Fashioned Off the beaten path Romantic Trendy Upscale Ambiance Labels
  23. 23. Inter-annotator Consensus [0.8, 1.0) [0.6, 0.8) [0.0, 0.6)
  24. 24. ICCs across Cities [0.8, 1.0) [0.6, 0.8) [0.0, 0.6)Color Legend
  25. 25. Ambiance across Cities – Correlation Analysis
  26. 26. Comparison between Cities ● Relatively few significant differences across cities ● Popular places in Seattle are perceived as less artsy compared to places in Barcelona. ● Popular places in Paris are perceived as less old fashioned com-pared to NYC and Seattle.
  27. 27. Comparison between Cities ● Popular places in Seattle are perceived as less artsy compared to places in Barcelona. ● Popular places in Paris are perceived as less old fashioned com- pared to NYC and Seattle. Findings from RQ2: Reliable estimates of ambiance can be obtained using social media images, suggesting the presence of visual cues to form place impressions. Most aggregate impressions of ambiance are similar across popular places in all cities
  28. 28. Future Work ● What specific cues are used to form place impressions? ● Color? Lighting? Spatial layout? Interior Design? ● Automatic recognition of ambiance ● Establishing links between visual cues and place ambiance
  29. 29. Q & A Email: dsantani@idiap.ch Twitter: @SabMayaHai

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