1 / 21

Many-to-One Boundary Labeling

Many-to-One Boundary Labeling. Hao-Jen Kao, Chun-Cheng Lin, Hsu-Chun Yen Dept. of Electrical Engineering National Taiwan University. Outline. Introduction Motivations Problem setting Our results Conclusion & Future work. Point features e.g., city. Line features e.g., river.

tex
Download Presentation

Many-to-One Boundary Labeling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Many-to-One Boundary Labeling Hao-Jen Kao, Chun-Cheng Lin, Hsu-Chun Yen Dept. of Electrical Engineering National Taiwan University

  2. Outline • Introduction • Motivations • Problem setting • Our results • Conclusion & Future work

  3. Point features • e.g., city • Line features • e.g., river • Area features • e.g., mountain Map labeling

  4. Type-opo leaders • Type-po leders • Type-s leaders (Bekos & Symvonis, GD 2005) Boundary labeling (Bekos et al., GD 2004) label site leader Min (total leader length) s.t. #(leader crossing) = 0 1-side, 2-side, 4-side

  5. Polygons labeling (Bekos et. al, APVIS 2006) Multi-stack boundary labeling (Bekos et. al, FSTTCS 2006) Variants

  6. Motivations • In practice, it is not uncommon to see more than one site to be associated with the same label • Ex1: The language distribution of a country • Each city  site • The main language used in a city  label • Ex2: Religion distribution in each state of a country • Ex3: The association or organization composed of some countries in the world

  7. Crossing problem Leader length problem Many-site-to-one-label boundary labeling (a.k.a. Many-to-one boundary labeling) • Type-opo leaders • Type-po leders • Type-s leaders • Main aesthetic criteria: • To minimize the leader crossings • To minimize the total leader length

  8. Our main results Note that c is a number depending on the sum of edge weights.

  9. Main assumption • Assumption • There are no two sites with the same x- or y- coordinates • When we consider the crossing problem for the labeling with type-opo leaders, only y-coordinates matter. 1 1 2 2 upward downward #(crossings) = 2 #(crossings) = 2

  10. Find an ordering s.t. #(crossing) is minimized. Fixed ordering #(crossings)  M #(crossings)  4M + #(self-contributed crossings) 1-side-opo crossing problem is NP-C • The Decision Crossing Problem (DCP) • DCP is NP-C. (Eades & Wormald, 1994) • DCP 1-side-opo crossing problem

  11. 3-approximation • Median algorithm (Eades & Wormald, 1994) • Median algorithm is 3-approximation of 1-side-opo crossing problem (The correctness proof is along a similar line of that of [Eades & Wormald, 1994]) Arbitrary Median algorithm

  12. Experimental result Brown booby Distribution of some animals in Taiwan: Taiwan hill partridge Masked palm civet Hawk Melogale moschata Bamboo partridge Chinese pangolin Mallard

  13. 2-side-opo crossing problem even when n1 = n2 Legal operations: Swapping two nodes between the two sides Change the node ordering in each side 1-side-opo crossing problem  2-side-opo crossing problem even when n1 = n2 +1 +1 2-side-opo crossing problem is NP-C even when n1 = n2 l1 r1 p1 l2 p2 r2 p3 r3 l3 pn ln rn pN

  14. 3(1+.301/c)-approximation • Max-Bisection Problem • There exists a 1.431-approximiation algorithm for the Max-Bisection problem (Ye, 1999). • By using the approximation algorithm for the Max-Bisection problem, we can find a 3(1+.301/c)-approximation for the 2-side-opo crossing problem, where c is a number depending on the sum of edge weights. # = n/2 # = n/2 weighted graph |V| = n Max (edge weight sum on the cut)

  15. Step 1. sites labels labels 1 1 1 1 3 1 Max-Bisection Complete weighted graph Less crossings Algorithm • Step 2. • Step 3. sites labels Median algorithm

  16. Brown booby Taiwan hill partridge Masked palm civet Melogale moschata Hawk Bamboo partridge Chinese pangolin Mallard Experimental result

  17. 1-side-po crossing problem is NP-C • 1-side-opo crossing problem  1-side-po crossing problem

  18. Greedy heuristic • Link the leftmost site and the sites with the same color • Experimental results

  19. Total leader length problem • For any number of sides and any type of leaders, minimizing the total leader length for many-to-one labeling can be solved in O(n2 log3n) time edge weight = Manhattan distance 3 1 1 2 4 2 3 4 complete weighted bipartite graph Find minimum weight matching

  20. Conclusion Note that c is a number depending on the sum of edge weights.

  21. Future work • Is there an approximation algorithm for the 1-side-po crossing problem? • Is the 2-side-po crossing problem tractable? • Is the 4-side many-to-one labeling tractable? • Can we simultaneously achieve the objective to minimize #(crossing) as well as minimize the total leader length?

More Related