Pairwise Geometric Matching for Large-Scale Object Retrieval
Spatial verification is a key step in boosting the performance of object-based image retrieval. It serves to eliminate unreliable correspondences between salient points in a given pair of images and is typically performed by analyzing the consistency of spatial transformations between the image regions involved in individual correspondences. In this paper, we consider the pairwise geometric relations between correspondences and propose a strategy to incorporate these relations at significantly reduced computational cost, which makes it suitable for large-scale object retrieval. In addition, we combine the information on geometric relations from both the individual correspondences and pairs of correspondences to further improve the verification accuracy. Experimental results on three reference datasets show that the proposed approach results in a substantial performance improvement compared to the existing methods, without making concessions regarding computational efficiency.
Code (0)
등록된 구현이 없습니다.
Tasks
Computational EfficiencyGeometric MatchingImage RetrievalObjectRetrievalSimilar Papers 제목 키워드 기반
PAIGE: PAirwise Image Geometry Encoding for Improved Efficiency in Structure-From-Motion
Large-scale Structure-from-Motion systems typically spend major computational effort on pairwise image matching and geometric verification in order to discover connected components in large-scale, unordered image collect…
3D Fragment Reassembly Using Integrated Template Guidance and Fracture-Region Matching
This paper studies matching of fragmented objects to recompose their original geometry. Solving this geometric reassembly problem has direct applications in archaeology and forensic investigation in the computer-aided re…
Boosting Multi-view Stereo with Late Cost Aggregation
Pairwise matching cost aggregation is a crucial step for modern learning-based Multi-view Stereo (MVS). Prior works adopt an early aggregation scheme, which adds up pairwise costs into an intermediate cost. However, we a…
BlockingGeometric MatchingTwo by Two: Learning Multi-Task Pairwise Objects Assembly for Generalizable Robot Manipulation
3D assembly tasks, such as furniture assembly and component fitting, play a crucial role in daily life and represent essential capabilities for future home robots. Existing benchmarks and datasets predominantly focus on …
3D AssemblyPose EstimationRobot ManipulationGeometric Polynomial Constraints in Higher-Order Graph Matching
Correspondence is a ubiquitous problem in computer vision and graph matching has been a natural way to formalize correspondence as an optimization problem. Recently, graph matching solvers have included higher-order term…
Graph Matching