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Bichromatic  Separating Circles Bichromatic  Separating Circles

Bichromatic Separating Circles - PowerPoint Presentation

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Bichromatic Separating Circles - PPT Presentation

Problem Given two sets of points R and B R ² where R n and B m Find the smallest circle containing all of R and as few points as possible from B ID: 707441

circle points separating event points circle event separating smallest circles time red edge point exit blue bound boundary enclosing

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Presentation Transcript

Slide1

Bichromatic

Separating CirclesSlide2

Problem

Given two sets of points,

R

and

B

R

² where |

R

| =

n

and |

B

| =

m

:

Find the smallest circle containing all of

R

and as few points as possible from

BSlide3

Example

Smallest enclosing circle

Smallest separating circleSlide4

Possible Applications

Communications jamming

Minimizing civilian casualties

Data set separationSlide5

Previous Work

Fisk - Pure separability in O(

nm

) time

O’Rourke et al. - Pure separability in O(

n+m) time using linear programmingLinear Programming methods taken from MeggidoSlide6

Previous Work

Hurtado

et al. – Color grouping within axis parallel rectangles and strips

Aronov

et al. – Separating red and blue sets using a lineSlide7

Possible Separating Circles

If it contains 3 points from

R

the answer is the smallest enclosing circle for

R

Must contain at least two points from RSlide8

No Less Than Two Red Points

Single red point on boundary - contradictionSlide9

Two Red Points

Two red points lying on the boundary of a circle

Farthest two red points since all red points must be contained in the circleSlide10

Farthest Neighbor

Voronoi

Diagram

An edge is the locus of all points that have the same two farthest points from

R

Can be thought of as a tree with the root being the center of the minimum enclosing circle of RSlide11

Finding the Boundary

Center circle on farthest Neighbor

Voronoi

edge

Find event point for each point in

B

Event point is defined as when a blue point enters or exits the circleSlide12

Finding the Boundary

Two red points and the edge of FVD that they defineSlide13

Finding the Boundary

Finding the event pointsSlide14

Finding the BoundarySlide15

The Algorithm

Compute the FVD for

R

For each of the O(

n

) edges of the diagram, we perform an event point sweepFind event points for all blue pointsSort in order of increasing distance from the red pointsCalculate # of blue points within the circleOnly need to increment/decrement after first countConstant time updateSlide16

Running Time/Space Analysis (Smallest Circle)

Computing the FVD for

R

takes O(

n

logn) time and uses O(n) spaceFor each of the O(n) edges of the diagram, we perform the sweepThis uses O(m) space and O(

mlogm) timeThus, overall we use O(n+m) space and O(nmlogm + nlogn) timeSlide17

Event Points

Sweep algorithm analyzes all event points

Each edge may have

O(m)

event points

As the circle grows, it will eventually enclose all blue points in the

halfspaceSlide18

Event Points

Each edge may have

O(m)

event pointsSlide19

Event Points

Each edge may have

O(m)

event pointsSlide20

Event Points

Intersection of

halfspaces

Place

O(m)

points within this region

All of those points will cause event points for each of the edgesSlide21

Exit Event Points

Size

of enclosing circle increases along path from root to leaf

Not necessary to analyze all event points

Only

analyze exit eventsSlide22

Exit Event Points

Each edge of

FVD(

R)

defines an exit region

Exit regions are disjoint

<=

m exit eventsSlide23

Counting Blue Points

Sweeping allowed count to be found in constant time

Use circular range countingSlide24

Running Time/Space Analysis (Smallest Circle) Second Algorithm

Find edge of

FVD(

R)

defining the exit region for each point in

BO(nm) timePerform O(m) circular range counting queriesO*(m1.5)

time and space* notation hides a polylogarithmic factorFaster than the sweeping algorithm if n=ω(√m) Slide25

Bound on the Number of Smallest Circles

There are

n

separating circles in the worst case

Lower boundSlide26

Bound on the Number of Smallest Circles

There are

n

separating circles in the worst case

Lower boundSlide27

Bound on the Number of Smallest Circles

There are

n

separating circles in the worst case

Upper bound

Center of smallest enclosing circle

Root to leaf path increases circle size, so smallest separating circles can only exist on disjoint root to leaf pathsSlide28

Largest Separating Circle

Use largest separating circle algorithm for purely separable sets as a subroutine

Remove all points from

B

that are inside circles with the minimum number of blue points encountered during the sweepSlide29

Largest Separating Circle

Subroutine takes

O((

n+m

)log(

n+m)) timeOverall running time O(m(n+m)log(n+m))