Photographer Paths: Sequence Alignment of Geotagged Photos for Exploration-based Route Planning

Download Photographer Paths: Sequence Alignment of Geotagged Photos for Exploration-based Route Planning

Post on 04-Jul-2015




1 download

Embed Size (px)


Slides for the talk I gave at CSCW 2013, held in San Antonio, TX, USA. The full paper reference is: El Ali, A., van Sas, S. & Nack, F. (2013). Photographer Paths: Sequence Alignment of Geotagged Photos for Exploration-based Route Planning. In proceedings of the 16th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '13), 2013, San Antonio, Texas. Paper link:


  • 1. Photographer Paths: Sequence Alignment of GeotaggedPhotos for Exploration-based Route Planning!Feb. 26, 2013 Abdallah Abdo El Ali Sicco van Sas Frank Nack h6p://

2. Outline!I.Introduc3on II. Photographer Paths III. User Evalua3on IV. Results V.Discussion & Future Work 2 3. Introduction3 4. 4 5. 5 6. Pffttt6 7. We dont always want to supply user preferences 7 8. Social and local interpreta3on of city places and routes 8 9. O-the-beaten track, social trails, 9 Lonely Planet! 10. Assump3on: Loca3ons of photographs are poten3ally interes3ng 10 11. But sequen3al property needs to be captured! 11 12. Sequence Alignment methods 12 13. Analysis of mobility behavior of city photographers: where photographers have been in what order they have been there how closely their movements parallel those of other photographers 13 By Keiichi Matsuda via supercolossal 14. Research Questions! How can walkable route plans be automaCcally generated for residents (and tourists) that would like to explore a city? And are these route plans desirable? Three factors: 1) Which data sources? 2) Which methods to generate routes? 3) User percep3ons compared to fastest and popular routes? 14 15. Photographer Paths!15 16. Approach! 1) Crawl Flickr geotags, 3mestamps 2) Map each geotag/loca3on in a sequence to a cell in a par33oned grid map 3) Mul3ple Sequence Alignment on photographer routes to nd aligned loca3on sequences These alignments are Photographer Route Segments (PRSs) 16 17. Dataset! Flickr geotagged photos within Amsterdam, The Netherlands Area: 17.3 km N-S and 24.7 km E-W (center) 5-year period (Jan. 2006 - Dec. 2010) Aeributes: owner ID photo ID date and 3me-stamp la3tude and longitude (street level accuracy) Database: 426,372 photos 17 18. Preprocessing! Sequence inference with following constraints: photo taken within 4 hours from previous photo and in same order minimum 2 or more dierent loca3ons (or nodes) early experiments determined 125 x 125m cells in center of Amsterdam grid suitable 1691 routes (average length of 9.92 loca3ons) 1130 unique photographers 18 19. Sequence Alignment! To nd photographer paths from Photographer Route Segments (PRSs), constraints set: PRS has minimum 4 photographers with minimum 2 aligned nodes/loca3ons !#**%Photographer Route Segments (PRSs)!!"#$% !"**% !+**%%&()*+$,*-.*)/*0$ !***%$**%##&% +%,-./.012,-314% 231 PRSs #**%!&% )%,-./.012,-314% (average length of 2.61 nodes) "%,-./.012,-314%"**% !"#$+**%!(% !*!%+%!*% !%)%*%+%)% "%%1)-.*$&2/342)0$ 19 20. PRSs in Amsterdam!20 21. PRS Aggregation! Modied Dijkstras shortest path algorithm &P1N1 P2N1 & #! P1N2!"#!"#$%StartP1N3P2N2 End21 22. PRS Aggregation to Crude Routes! PRSs CM Photographer RouteWW Photographer Route22 23. User Evaluation23 24. Laboratory Study Design! ~45 min. Quan3ta3ve/Qualita3ve lab-based study 15 par3cipants (10 m, 5 f) aged between 21-35 (M = 29.2; SD = 3.3) Interac3ve web-based prototype route planner Expert route evalua3on by city residents (lived in Amsterdam > 1 year) Plain routes to avoid informa3on type bias 24 25. Laboratory Study Design! Two scenarios: Route 1: Central Sta3on to Museumplein anernoon scenario favoring explora3on Route 2: Waterlooplein to Westerkerk evening scenario favoring eciency Baseline comparisons: Photo Density (PD) route: highest density of photos (over 5 year period) in grid cells along route Google Maps (GM) route: shortest route between two loca3ons Counterbalanced within-subject design Route Varia3on (IV): Photographer Paths vs. Photo Density vs. Google Maps 25 26. Central Station to Museumplein (CM)!Photographer PathsPhoto Density Google Mapsroute (5.36 km)route (3.83 km) route (3.35 km)26 27. Waterlooplein to Westerkerk (CM)! Photographer Paths route (2.28 km)Photo Density route (2.60 km)Google Maps route (1.59 km)27 28. Laboratory Study Design! Data collected: 1.AerakDi2 (Hassenzahl, 2003) UX ques3onnaire responses [7-point seman3c dieren3al scale]: Usability, Hedonic Quali3es (Iden3ty, S3mula3on), Aerack3veness 2.Two-part semi-structured interviews Part 1: Route preferences, feedback on Photographer Paths Part 2: Inves3ga3on of visualized informa3on types (visualized info type handouts): a) Google maps b) Color coded PRSs (PP route) c) Density geopoints (PD route) d) Thumbnail photo geopoints e) Foursquare POIs 28 29. a) d) b)e) c)29 30. Web Survey Study! Short web-based survey for CM and WW routes and varia3ons Basic demographics collected: age, gender, years in Amsterdam Sta3c route images, no counterbalancing 82 par3cipants (55 m, 27 f) aged between 17-62 (M= 27.6; SD= 6.1) Most lived in Amsterdam for more than 3 years (44/82) Some between 1-3 years (15/82) Less than a year (11/82) Only visited before (12/82) 30 31. Results31 32. AttrakDiff2 ! Central Station to Museumplein (CM) Route "# ************* * $# %# !"#$% !%# !$# !"# ()*+),-#./)0123#4.5# 6789:1-#./)0123#!#;87:,23# 6789:1-#./)0123#!#=>()-,?7:7@@#4=AA5# 46.!;5#