A Geometric Correspondence Feature Based-Mismatch Removal in Vision Based-Mapping and Navigation
Images with large-area repetitive texture, significant viewpoint, and illumination changes as well as occlusions often induce high-percentage keypoint mismatches, affecting the performance of vision-based mapping and navigation. Traditional methods for mismatch elimination tend to fail
when the percentage of mismatches is high. In order to remove mismatches effectively, a new geometry-based approach is proposed in this paper, where Geometric Correspondence Feature (GCF) is used to represent the tentative correspondence. Based on the clustering
property of GCFs from correct matches, a new clustering algorithm is developed to identify the cluster formed by the correct matches.
With the defined quality factor calculated from the identified cluster, a Progressive Sample Consensus (PROSAC) process integrated with hyperplane-model is employed to further eliminate mismatches.
Extensive experiments based on both simulated and real images in indoor and outdoor environments have demonstrated that the proposed approach can significantly improve the performance of mismatch elimination in the presence of high-percentage mismatches.
With the defined quality factor calculated from the identified cluster, a Progressive Sample Consensus (PROSAC) process integrated with hyperplane-model is employed to further eliminate mismatches.
Extensive experiments based on both simulated and real images in indoor and outdoor environments have demonstrated that the proposed approach can significantly improve the performance of mismatch elimination in the presence of high-percentage mismatches.
Document Type: Research Article
Publication date: 01 October 2017
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
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