Pictorial and Apictorial Polygonal Jigsaw Puzzles from Arbitrary Number of Crossing Cuts

Peleg Harel, Ofir Itzhak Shahar, Ohad Ben-Shahar

Research output: Contribution to journalArticlepeer-review

Abstract

Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping unordered visual fragments, is fundamental to numerous applications, and yet most of the literature of the last two decades has focused thus far on less realistic puzzles whose pieces are identical squares. Here we formalize a new type of jigsaw puzzle where the pieces are general convex polygons generated by cutting through a global polygonal shape/image with an arbitrary number of straight cuts, a generation model inspired by the celebrated Lazy caterer’s sequence. We analyze the theoretical properties of such puzzles, including the inherent challenges in solving them once pieces are contaminated with geometrical noise. To cope with such difficulties and obtain tractable solutions, we abstract the problem as a multi-body spring-mass dynamical system endowed with hierarchical loop constraints and a layered reconstruction process. We define evaluation metrics and present experimental results on both apictorial and pictorial puzzles to show that they are solvable completely automatically.

Original languageEnglish
JournalInternational Journal of Computer Vision
DOIs
StateAccepted/In press - 1 Jan 2024

Keywords

  • Computational jigsaw puzzle solving
  • Crossing cuts
  • Hierarchical loops
  • Lazy caterer
  • Loopy constraints
  • Pictorial and apictorial puzzles

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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