The Connect-The-Dots family of puzzles

In this paper we introduce several innovative variants on the classic Connect-The-Dots puzzle. We study the underlying geometric principles and investigate methods for the automatic generation of high-quality puzzles from line drawings. Specifically, we introduce three new variants of the classic Connect-The-Dots puzzle. These new variants use different rules for drawing connections, and have several advantages: no need for printed numbers in the puzzle (which look ugly in the final drawing), and perhaps more challenging "game play", making the puzzles suitable for different age groups. We study the rules of all four variants in the family, and design principles describing what makes a good puzzle. We identify general principles that apply across the different variants, as well as specific implementations of those principles in the different variants. We make these mathematically precise in the form of criteria a puzzle should satisfy. Furthermore, we investigate methods for the automatic generation of puzzles from a plane graph that describes the input drawing. We show that the problem of generating a good puzzle --one satisfying the mentioned criteria-- is computationally hard, and present several heuristic algorithms. Using our implementation for generating puzzles, we evaluate the quality of the resulting puzzles with respect to two parameters: one for similarity to the original line drawing, and one for ambiguity; i.e. what is the visual accuracy needed to solve the puzzle.

[1]  Leonidas J. Guibas,et al.  Approximating Polygons and Subdivisions with Minimum Link Paths , 1991, ISA.

[2]  Sancho Salcedo-Sanz,et al.  Automated generation and visualization of picture-logic puzzles , 2007, Comput. Graph..

[3]  Robert E. Tarjan,et al.  A Linear-Time Algorithm for Testing the Truth of Certain Quantified Boolean Formulas , 1979, Inf. Process. Lett..

[4]  Frédéric Maire,et al.  Evolutionary Game Design , 2011, IEEE Transactions on Computational Intelligence and AI in Games.

[5]  David Eppstein,et al.  The Crust and the beta-Skeleton: Combinatorial Curve Reconstruction , 1998, Graph. Model. Image Process..

[6]  M. V. Kreveld,et al.  Topologically correct subdivision simplification using the bandwidth criterion , 1998 .

[7]  M. Iri,et al.  Polygonal Approximations of a Curve — Formulations and Algorithms , 1988 .

[8]  David Eppstein,et al.  On Nearest-Neighbor Graphs , 1992, ICALP.

[9]  G.S. Brodal,et al.  Dynamic planar convex hull , 2002, The 43rd Annual IEEE Symposium on Foundations of Computer Science, 2002. Proceedings..

[10]  Craig S. Kaplan,et al.  Image-guided maze construction , 2007, SIGGRAPH 2007.

[11]  John Hart,et al.  ACM Transactions on Graphics , 2004, SIGGRAPH 2004.

[12]  S. Colton Automated Puzzle Generation , 2002 .

[13]  Hyun Joon Shin,et al.  SPOID: a system to produce spot-the-difference puzzle images with difficulty , 2013, The Visual Computer.

[14]  Alexandru Iosup,et al.  Procedural content generation for games: A survey , 2013, TOMCCAP.

[15]  Michael Burch,et al.  Evaluating Partially Drawn Links for Directed Graph Edges , 2011, GD.

[16]  W. S. Chan,et al.  Approximation of Polygonal Curves with Minimum Number of Line Segments or Minimum error , 1996, Int. J. Comput. Geom. Appl..

[17]  Joe Marks,et al.  An empirical study of algorithms for point-feature label placement , 1995, TOGS.

[18]  J. O'Rourke,et al.  Connect-the-dots: a new heuristic , 1987 .

[19]  Joseph S. B. Mitchell,et al.  Simplifying a polygonal subdivision while keeping it simple , 2001, SCG '01.

[20]  Jong-Chul Yoon,et al.  A Hidden‐picture Puzzles Generator , 2008, Comput. Graph. Forum.

[21]  Kurt Mehlhorn,et al.  Curve reconstruction: connecting dots with good reason , 1999, SCG '99.

[22]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[23]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.