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A Robust Strategy for Handling Linear Features in Topologically Consistent Polyline Simplification. da Silva, Adler C. G. Wu, Shin-Ting {acardoso,ting}@dca.fee.unicamp.br. Department of Computer Engineering and Industrial Automation (DCA)
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A Robust Strategy for Handling Linear Features in Topologically Consistent Polyline Simplification da Silva, Adler C. G. Wu, Shin-Ting {acardoso,ting}@dca.fee.unicamp.br Department of Computer Engineering and Industrial Automation (DCA) School of Electrical and Computer Engineering (FEEC) State University of Campinas (UNICAMP) GEOINFO 2006
Topics • Motivation • Polyline Simplification • Consistent Simplification • Problem • Objective • Solution • Results • Concluding Remarks • Future Work GEOINFO 2006
Motivation • Create a topologically consistent simplification algorithm that • Handles all map features together • Generates better visual results • Achieves efficient processing • Produces scale independent maps GEOINFO 2006
Polyline Simplification Original Map Simplified Map 50,000 points 2,000 points Source: Digital Chart of the World Server (www.maproom.psu.edu/dcw) GEOINFO 2006
Polyline Simplification • Common problem in most algorithms • Loss of “Topological Consistency” • Cause: they take the polyline in isolation, without considering the features in its vicinity GEOINFO 2006
Example: RDP Algorithm • Maximum tolerable distance () • It adds the farthest vertex from line segment GEOINFO 2006
Example: RDP Algorithm • Problem with big tolerance GEOINFO 2006
Consistent Simplification • A topologically consistent polyline simplification algorithm must • Keep features in the correct side • Avoid intersections between features • Avoid self-intersections • The algorithm may • Simplify one polyline considering the features in its vicinity (simplification in context) • Simplify the complete collection of polylines together (global simplification) GEOINFO 2006
State of the Art • de Berg et al., 1998 • Simplification is viewed as an optimization problem • A single polyline is simplified in context • It handles only polylines that are part of a polygon • Saalfeld, 1999 • It is a improvement of RDP for recovering topology • A single polyline is simplified in context • It also handles polylines that are not part of a polygon • Inconsistency is removed by inserting more vertices • van der Poorten and Jones, 1999 / 2001 • The polylines of the map are simplified together • Based on Constrained Delaunay Triangulation • Topology is implicitly preserved • Relatively slow (10min for 30,000 vertices) GEOINFO 2006
Problem • de Berg et al. and Saalfeld handle a linear feature as a point feature • When handling a line segment, they consider that intersections can be avoided if the side of its vertices is preserved Problem with polygons Problem with polylines GEOINFO 2006
de Berg et al.’s Strategy • A polyline is part of a polygon • They formalize consistency of a point with respect to a polygon • de Berg et al.’s algorithm adds other restrictions that avoid the problematic cases GEOINFO 2006
Saalfeld’s Strategy • He generalizes the consistency of polygons to polylines • Compute sidedness: count the number of crossings of a ray from the point with P and P’ • Odd = wrong side • Even = correct side • Triangle Inversion Property • The insertion of a vertex changes only the sidedness of the points inside the triangle • Used to update sidedness of points GEOINFO 2006
Saalfeld’s Algorithm 1st step: RDP algorithm until condition is satisfied 2nd Step: further insertions until sidedness and conditions are satisfied GEOINFO 2006
Objective • General context • Develop a topologically consistent simpli-fication algorithm using Saalfeld’s strategy • Remove locally inconsistencies • Contribution of this work • Theoretical solution • Study on consistency to avoid (self-) intersections by taking into consideration only vertices of polylines • Practical solution • Replace the triangle inversion test by a robust test GEOINFO 2006
Theoretical Analysis • An inconsistency occurs whenever a subpolyline intersects the simplifying segment of another subpolyline • Example: Pkj intersects vivk, which is the simplifying segment of Pik Region with problem GEOINFO 2006
Theoretical Solution • Consider each subpolyline and its simplifying segment separately • Example: Sidedness of p1 is evaluated with respect to (Pik, vivk) and (Pkj, vkvj). GEOINFO 2006
Practical Solution • Pre-processed array of crossings with Pij • Number of crossings is very small • begin points to the first element • end points to the element after the last one • Number of crossings = (begin-end)+(crossing with segment vivj) GEOINFO 2006
Practical Solution • When inserting a vertex • Just update pointers begin and end (O(log n)) • Store a reference to original array GEOINFO 2006
Results: Synthetic Data • Intersections Original Data Triangle Inversion Array of Crossings Polylines Polygons GEOINFO 2006
Results: Synthetic Data • Self-intersections Original Data Triangle Inversion Array of Crossings Polylines Polygons GEOINFO 2006
Results: Processing Time Source: Digital Chart of the World Server (www.maproom.psu.edu/dcw) GEOINFO 2006
Results: Processing Time • Equivalent processing time • Insert a few more vertices for correcting inconsistencies GEOINFO 2006
Concluding Remarks • Mistake in consistent simplification algorithms • Handle linear features as point features • Theoretical solution • Handle separately each subpolyline and its simplifying line segment • Practical solution (for Saalfeld’s algorithm) • Pre-processed array of crossings • Complete elimination of inconsistencies • Equivalent processing time • A few more vertices are inserted to recover topology GEOINFO 2006
Future Work • The consistent simplification algorithm • Handles polylines in a global simplification • Considers only vertices that are currently in simplified polylines • Inserts less vertices better visual results • Achieves faster processing • Can be used with many isolated algorithms • Produce scale independent maps GEOINFO 2006
The End Thank You! GEOINFO 2006