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Radu Mariescu-Istodor 10.2.2014

LAMI 1. User Oriented Trajectory Similarity Search 2. Calibration-free Localization using Relative Distance Estimations 3. From GPS Traces to a Routable Road Map. Radu Mariescu-Istodor 10.2.2014. Similarity Search. Naive solution is to compare Every pair of points ( 10 8 )

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Radu Mariescu-Istodor 10.2.2014

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  1. LAMI1. User Oriented Trajectory Similarity Search 2. Calibration-free Localization using Relative Distance Estimations 3. From GPS Traces to a Routable Road Map RaduMariescu-Istodor 10.2.2014

  2. Similarity Search Naive solution is to compare Every pair of points (108) From reference route and Every route in DB (105) Average route length ~1000 points. 108 haversines ~ 30 minutes

  3. Limiting the space R-tree indexed points => easy to conduct range checks Naive solution is to compare Every pair of points (108) From reference route and Every route in DB (105) the routes that have at least one point in one of the squares

  4. Reducing range check calculations Grouping several squares into a bounding rectangle

  5. How to group? Dead Space Dead Space Limiting the Dead Space as much as possible

  6. How to limit the Dead Space?

  7. Longest Common Subsequence O(N2) Heaviest Common Subsequence

  8. User Oriented Similarity User defined Regions Heaviest Common Subsequence

  9. Improve speed of HCSS Heaviest Grouped Subsequence HCSS ≤ HGSS 1. HGSS = 492 2. HGSS = 452 3. HGSS = 412 4. HGSS = 301 ………………. HCSS ?

  10. Purpose How to calculate the position of mobile devices that do not posses a GPS sensor

  11. Centroid and Fingerprinting

  12. How it works? Cell1=50% Cell2=80% Cell3=60% GPS signature

  13. How it works? Common Cells = 2 Uncommon Cells = 3 Spearman = ? Feature : Cell1=50% Cell2=80% Cell3=60% Cell1=80% Cell3=20% Cell5=30% Cell6=20% (Experimentally deduced)

  14. Regression Formula (Experimentally deduced) Fitted from GPS phones Features ={Common, Uncommon, Spearman}

  15. Estimating locations

  16. Objective: Road Network from GPS Tracks

  17. Merging nearby trajectories Gravity

  18. Merging nearby trajectories Gravity Spring Resultant force applied in small iterations until change insignificant

  19. Traces of opposite directions Method so far Desired output:

  20. Repelling force ≠ ? Sign tells if same direction or not

  21. Solution

  22. Banding issue expecting Gaussian Distribution

  23. Matching the Gaussians expecting Gaussian Distribution Finding centroids gives number of bands

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