Metro Transit-Centric Visualization for City Tour Planning

Pio Claudio and Sung-Eui Yoon

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Motivation

Tourist Destinations MapMetro Map

Switching between maps forces users to manually map points between different coordinate spaces

Display a holistic combined view of a transportation map and a tourist map

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Outline

• Motivation

• Related Work

• Our Approach

• Results

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Related Work

• Automatic Generation of Octilinear Metro Layouts– Mass-Spring[Hong et al. 06], Hill

Climbing[Stott et al. 11]

– Mixed Integer Programming: Nöllenburg et al. 2011

• Map Warping– Image Warping: Böttger et al. 2008

– Helmert Transform: Jenny et al. 2011

http://davis.wpi.edu/~matt/courses/morph/2d.htm

http://designmuseum.org/design/london-transport

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• Combining Different Maps

Related Work

Böttger et al, 2008Reilly et al., 2004

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Our Approach

INPUT: Metro MapINPUT: Tourist DestinationsOctilinear LayoutMap WarpingDestinations Summary

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Framework

POI Data

Run-time Map

Hierarchical Clustering

Map WarpingOctilinear Layout

Visual Worth

Trip Websites

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Determining Popular Regions

Focus +

Context

Wider spaces to popular regions

Graphical Fisheye Views of Graphs. Sarkar et al.

Which are popular regions?

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Determining Popular Regions: Visual Worth

• Kernel Density Estimation

1. Tourist destinations (Points-of-Interest POI)

2. Highly ranked tourist destinations (rank r)

3. Nearby metro-stations (proximity ρ): POI

Visual Worthhighlow

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Framework

POI Data

Run-time Map

Hierarchical Clustering

Map WarpingOctilinear Layout

Trip Websites

Visual Worth

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Octilinear Layout Computation

• Why Octilinear Layout?– Clean and readable schematic representation

• Mixed-Integer Programming [Nöllenburg et al. 2011]

– A set of design constraints are satisfied to find a global solution to layout optimization

Input Variable

Apply variable edge lengths according to visual worth

Uniform Octilinear

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Framework

POI Data

Run-time Map

Hierarchical Clustering

Map WarpingOctilinear Layout

Trip Websites

Visual Worth

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Map Warping

• Put tourist map elements in a single map space• Map warping

– Use the metro stations as control points– Solve for affine transformation parameters– Apply transformation and interpolation to original map points

Input Warped Map

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Framework

POI Data

Run-time Map

Hierarchical Clustering

Map WarpingOctilinear Layout

Trip Websites

Visual Worth

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• Displaying all tourist destinations will clutter the map• Display only relevant destinations at a given view

configuration (visual worth)

Hierarchical Clustering

• Run a hierarchical clustering algorithm [Goldberger2008]

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Runtime Map

• Determine a graph cut which displays largest clusters fitting the view window

• Display top N rated clusters (visual worth)

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Results

Default zoom level Zoomed-in view

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Results: User Study

0%

20%

40%

60%

80%

100%

36% 37%

24%

46%39%

34%

64% 63%

76%

54%61%

66%

Other Ours

Pre

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Pe

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ntag

e

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Summary

• Holistic visualization technique

– Combines tourist destinations map

– transportation (metro) map

• Octilinear Layout for effective navigation

• Identify and highlight popular tourist areas

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• Connecting paths to POIs

• Adaptive map layout for different display sizes

Future work

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• NRF-2013R1A1A2058052

• DAPA/ADD (UD110006MD)

• MEST/NRF (2013-067321)

• IT R&D program of MOTIE/KEIT [10044970]

Acknowledgements

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Thank you for listening!

Paper, videos,

source code(coming soon)!

Visit our project homepage:

sglab.kaist.ac.kr/MetroVis