Technology Category
Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal ReasoningSearch and Optimization: Mixed Discrete/Continuous SearchConstraint Satisfaction and Optimization: Other Foundations of Constraint Satisfaction
Pairwise Alignment & Compatibility for Arbitrarily Irregular Image Fragments
🤖 AI Summary
Existing fragment reassembly methods often rely on assumptions of regular geometric shapes, limiting their effectiveness in real-world scenarios—such as archaeology—where fragments exhibit highly irregular geometries. To address this, we propose a hybrid geometric-image compatibility modeling framework that requires no prior assumptions about shape, size, or content. Our approach comprises three key components: (1) a generative model simulating archaeological erosion to produce realistic irregular fragments; (2) a pairwise discriminative mechanism jointly optimizing edge-based geometric alignment and local texture feature matching; and (3) a puzzle-oriented, neighborhood-level evaluation metric. Integrated into an end-to-end archaeological jigsaw solving pipeline, our method achieves state-of-the-art performance on the RePAIR 2D benchmark—improving neighborhood accuracy by +4.2% and recall by +5.8%. It significantly enhances robustness and accuracy in compatibility assessment for geometrically complex fragments.
Technology Category
Application Category
📝 Abstract
Pairwise compatibility calculation is at the core of most fragments-reconstruction algorithms, in particular those designed to solve different types of the jigsaw puzzle problem. However, most existing approaches fail, or aren't designed to deal with fragments of realistic geometric properties one encounters in real-life puzzles. And in all other cases, compatibility methods rely strongly on the restricted shapes of the fragments. In this paper, we propose an efficient hybrid (geometric and pictorial) approach for computing the optimal alignment for pairs of fragments, without any assumptions about their shapes, dimensions, or pictorial content. We introduce a new image fragments dataset generated via a novel method for image fragmentation and a formal erosion model that mimics real-world archaeological erosion, along with evaluation metrics for the compatibility task. We then embed our proposed compatibility into an archaeological puzzle-solving framework and demonstrate state-of-the-art neighborhood-level precision and recall on the RePAIR 2D dataset, directly reflecting compatibility performance improvements.
Problem
Research questions and friction points this paper is trying to address.
Solving jigsaw puzzles with irregular real-life fragment shapes
Computing optimal alignment without shape or content assumptions
Improving compatibility for archaeological fragment reconstruction
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hybrid geometric and pictorial alignment approach
Novel image fragmentation and erosion model
Archaeological puzzle-solving framework integration
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