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 (108)
From reference route and Every route in DB (105)
Average route length ~1000 points.
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
Reducing range check calculations
Grouping several squares into a bounding rectangle
How to group?
Dead Space
Dead Space
Limiting the Dead Space as much as possible
How to limit the Dead Space?
Longest Common Subsequence
Heaviest Common Subsequence
User Oriented Similarity
User defined
Regions
Heaviest Common Subsequence
Improve speed of HCSS
HCSS ≤ HGSS
1. HGSS = 492
2. HGSS = 452
3. HGSS = 412
4. HGSS = 301
……………….
HCSS ?
Purpose
How to calculate the position of mobile devices
that do not posses a GPS sensor
Centroid and Fingerprinting
How it works?
Cell1=50%
Cell2=80%
Cell3=60%
GPS signature
How it works?
Cell1=50%
Cell2=80%
Cell3=60%
Common Cells
Feature : Uncommon Cells
Spearman
(Experimentally deduced)
Cell1=80%
Cell3=20%
Cell5=30%
Cell6=20%
=2
=3
=?
Regression Formula
(Experimentally deduced)
Fitted from GPS phones
Features ={Common, Uncommon, Spearman}
Estimating locations
Objective: Road Network from GPS Tracks
Merging nearby trajectories
Gravity
Merging nearby trajectories
Gravity
Spring
Resultant force applied in small iterations
until change insignificant
Traces of opposite directions
Method so far
Desired output:
Repelling force
≠
Sign tells if
same direction or not
?
Solution
Banding issue
expecting
Gaussian
Distribution
Matching the Gaussians
expecting
Gaussian
Distribution
Finding centroids
gives
number of bands