Solving Jigsaw Puzzles with Linear Programming

11/13/2015
by   Chris Russell, et al.
0

We propose a novel Linear Program (LP) based formula- tion for solving jigsaw puzzles. We formulate jigsaw solving as a set of successive global convex relaxations of the stan- dard NP-hard formulation, that can describe both jigsaws with pieces of unknown position and puzzles of unknown po- sition and orientation. The main contribution and strength of our approach comes from the LP assembly strategy. In contrast to existing greedy methods, our LP solver exploits all the pairwise matches simultaneously, and computes the position of each piece/component globally. The main ad- vantages of our LP approach include: (i) a reduced sensi- tivity to local minima compared to greedy approaches, since our successive approximations are global and convex and (ii) an increased robustness to the presence of mismatches in the pairwise matches due to the use of a weighted L1 penalty. To demonstrate the effectiveness of our approach, we test our algorithm on public jigsaw datasets and show that it outperforms state-of-the-art methods.

READ FULL TEXT

page 2

page 6

page 7

research
01/15/2019

A linear programming approach to the tracking of partials

A new approach to the tracking of sinusoidal chirps using linear program...
research
01/17/2022

Learning to Reformulate for Linear Programming

It has been verified that the linear programming (LP) is able to formula...
research
12/12/2019

A scaling-invariant algorithm for linear programming whose running time depends only on the constraint matrix

Following the breakthrough work of Tardos in the bit-complexity model, V...
research
12/02/2019

Relating lp regularization and reweighted l1 regularization

We propose a general framework of iteratively reweighted l1 methods for ...
research
11/26/2022

Equity Promotion in Public Transportation

There are many news articles reporting the obstacles confronting poverty...
research
06/15/2021

Improving Search by Utilizing State Information in OPTIC Planners Compilation to LP

Automated planners are computer tools that allow autonomous agents to ma...
research
10/17/2022

Sufficient Exploration for Convex Q-learning

In recent years there has been a collective research effort to find new ...

Please sign up or login with your details

Forgot password? Click here to reset