Name
Title | ||
|---|---|---|
A Memetic Algorithm for Matching Spatial Configurations With the Histograms of Forces |
Abstract | ||
|---|---|---|
In this paper, we present an approach for modeling and comparing small sets of 2-D objects based on their spatial relationships. This situation can arise in the conflation of a hand- or machine-drafted map to a satellite image, or in the correspondence problem of matching two images taken under different viewing conditions. We focus on the specific problem of matching a sketched map containing several 2-D objects to hand-segmented satellite imagery. We define a similarity measure between the spatial configurations of two object sets, which uses attributed relational graphs to represent scene information. Objects are represented as graph nodes and edges are defined by the histograms of forces between object pairs. We develop a memetic algorithm based on a $(\\mu+\\lambda)$ evolution strategy to solve this scene-matching problem with three domain-specific local search operators that are compared experimentally. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TEVC.2012.2226889 | Evolutionary Computation, IEEE Transactions |
Keywords | Field | DocType |
evolutionary computation,geophysical image processing,graph theory,image matching,natural scenes,search problems,2D object modeling,attributed relational graphs,domain-specific local search operators,evolution strategy,force histograms,graph edges,graph nodes,hand-drafted map,hand-segmented satellite imagery,image matching,machine-drafted map,memetic algorithm,scene information representation,scene-matching problem,similarity measure,sketched map matching,spatial configuration matching,spatial configurations,spatial relationships,viewing conditions,Attributed relational graph (ARG),histogram of forces (HoF),memetic algorithms,scene matching,text-to-sketch $({rm T}_{2}{rm S})$ | Graph theory,Memetic algorithm,Conflation,Mathematical optimization,Similarity measure,Evolution strategy,Artificial intelligence,Local search (optimization),3-dimensional matching,Correspondence problem,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
17 | 4 | 1089-778X |
Citations | PageRank | References |
6 | 0.45 | 24 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew R. Buck | 1 | 13 | 3.35 |
| James M. Keller | 2 | 3201 | 436.69 |
| Marjorie Skubic | 3 | 1045 | 105.36 |