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SuperPoint features in endoscopy
[article]
2022
arXiv
pre-print
There is often a significant gap between research results and applicability in routine medical practice. This work studies the performance of well-known local features on a medical dataset captured during routine colonoscopy procedures. Local feature extraction and matching is a key step for many computer vision applications, specially regarding 3D modelling. In the medical domain, handcrafted local features such as SIFT, with public pipelines such as COLMAP, are still a predominant tool for
arXiv:2203.04302v1
fatcat:yfe7ypdp55durhgknbzp43wtgq