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## Approximate Matching of Polygonal Shapes

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**Approximate Matching of Polygonal Shapes**Speaker: Chuang-Chieh Lin Advisor: Professor R. C. T. Lee National Chi-Nan University CSIE in National Chi-Nan University**Outline**• Introduction • Determine the Hausdorff-distance • On a fixed translation & Davenport-Schinzel sequences • Pseudo-optimal solutions • References CSIE in National Chi-Nan University**Introduction**• Problem: For two given simple polygons P and Q, the problem is to determine a rigid motion I of Q giving the best possible match between P and Q, i.e. minimizing the Hausdorff-distance between P and I(Q) • Input: Two polygons P and Q • Output: An isometry I such that the Hausdorff-distance between P and I(Q) • Generally, + t, where t = <tx, ty> is a translation vector. CSIE in National Chi-Nan University**Determine the Hausdorff-distance (1/4)**• The Hausdorff-distance between P and I(Q) is defined as: , where , d(x, y)is the Euclidean distance in the plane. • How can we determine the Hausdorff-distance between two polygons? • By Voronoi diagrams [A83] Y X y1 x1 9 x2 7 y2 CSIE in National Chi-Nan University**Determine the Hausdorff-distance (2/4)**• Examples: [F87] & [Y87] CSIE in National Chi-Nan University**Determine the Hausdorff-distance (3/4)**• Note that the Voronoi edge can be a parabolic edge when a point meets a line segment. [F87] & [Y87] L x parabolic edge CSIE in National Chi-Nan University**Determine the Hausdorff-distance (4/4)**• Why do we adopt Voronoi diagrams? • Lemma: is either at some vertex of Q or at some intersection point of Q with some Voronoi-edgee of P having either the smallest or largest x-coordinate among the intersection points of Q with e. [ABB91] P Q CSIE in National Chi-Nan University**On a fixed translation & Davenport-Schinzel sequences (1/3)**• Suppose the isometry It = t for t = (t, 0), A is a point or a line segment of P, e/ is a Voronoi-edge of P bounding the Voronoi-cell C, and e is an edge of Q. • When we move polygon Q through a vector t, we need to analyze the Hausdorff-distances. These distances are “dynamic” and can be formed as distance functions. From the previous lemma, we know that is the maximum of these function above at some t.[ABB91] & [A85] e/ A e C t CSIE in National Chi-Nan University**On a fixed translation & Davenport-Schinzel sequences (2/3)**• In order to determine , we have to apply the theory of Davenport-Schinzel sequence to find the upper envelope of these functions. [AS95] • As the figure above, the upper envelope of these functions is the function drawn red. We define (1, 3, 2, 4) to be the upper-envelope sequence of these functions. f4 f1 f2 f3 t 1 3 2 4 CSIE in National Chi-Nan University**On a fixed translation & Davenport-Schinzel sequences (3/3)**• Why do we use the concept of Davenport-Schinzel sequence (We denote it as DS(n, s)-sequence)? • From a theorem (see [AS95]), we can obtain that the complexity of finding upper-envelope of univariate functions can be viewed as the maximum length of possible DS(n, s)-sequences. • The complexity in this case is , where p is the number of vertices of P and q is the number of vertices of Q. [ASS89] • In addition, Davenport-Schinzel sequences have many geometric applications which relate to computing envelopes. CSIE in National Chi-Nan University**Pseudo-optimal solutions (1/4)**• What is a Pseudo-optimal solution? • An algorithm is said to produce a pseudo-optimal solution, if and only if there is a constant c > 0 such that on input P, Q the algorithm finds a translation (isometry) I with where δis the minimal Hausdorff-distance determined by the optimal solution. CSIE in National Chi-Nan University**Y**C P D I(Q) F A rI (Q) yP B X rP E xP Pseudo-optimal solutions (2/4) – Without rotations Let where xP (yP) is the smallest x-coordinate (y-coordinate) of all points in P (Q). Let , We can easily obtain Since we will get . . Therefore, if maps rI(Q) onto rP , we will obtain a pseudo-optimal solution, i.e. . CSIE in National Chi-Nan University**Pseudo-optimal solutions (3/4) – Allowing rotations**• For another idea, we may transform polygons P and Q into convex hulls and respectively, and find the centroids SP and SQof the edges of and respectively. • Why? A centroid of a polygon never changes under rotations. • SP can be calculated as where is a natural parameterization of such that the length from point α(0) to α(l) equals l, and is the length of . CSIE in National Chi-Nan University**Pseudo-optimal solutions (4/4)**• Lemma: • If an isometry gives a minimal among the ones mapping SQ onto SP, we can obtain that • The angle of rotation, which gives the pseudo-optimal solution , can be determined by a technique analogous to the dynamic distance functions. The time complexity is still [ABB91] & [A85] & [ASS89] • However, has been improved to for any c > 1. [S88] CSIE in National Chi-Nan University**References**• [A83] A Linear Time Algorithm for the Hausdorff-distance between Convex Polygons, Atallah, M. J., Information Processing Letters, Vol. 17, 1983, pp. 207-209. • [A85] Some Dynamic Computational Geometry Problems, Atallah, M. J., Comput. Math. Appl., Vol. 11, 1985, pp. 1171-1181. • [ABB91] Approximate Matching of Polygonal Shapes, Alt, H. Behrends, B. and Blömer, J., In proceedings of 7th Annual ACM Symp. on Computational Geometry, 1991, pp. 186-193. • [AS95] Davenport-Schinzel Sequences and Their Geometric Applications, Agarwal, P. K. and Sharir, M., Department of Computer Science, Duke University, Durham, North Carolina, 27708-0129, September 1, 1995. • [ASS89] Sharp Upper bound and Lower Bound on the Length of General Davenport-Schinzel Sequences, Agarwal, P. K., Sharir, M. and Shor, P., Journal of Combinatorial Theory Series A, Vol. 52, 1989, pp. 228-274. • [F87] A Sweepline Algorithm for Voronoi Diagrams, Forrune, S., Algorithmica, Vol. 2, 1987, pp. 153-174. • [S88] Űber die Bitkomplexität der ε- Kongruenz, Diplomarbeit, Fachbereich Informatik, Universität des Saarlandes, 1988. • [Y87] An O(n log n) Algorithm for the Voronoi diagram of a Set of Simple Curve Segments, Yap, C. K., Discrete Computaional Geometry, Vol. 2, 1987, pp. 365-393. Thank you. CSIE in National Chi-Nan University