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arXiv 2012.15343cs.CV

Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School(马蒂诺斯生物医学成像中心、麻省总医院、哈佛医学院);Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology(麻省理工学院计算机科学与人工智能实验室(CSAIL));Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London(伦敦大学学院惠康/EPSRC介入与外科科学中心);Centre for Medical Image Computing, University College London(伦敦大学学院医学图像计算中心);KU Leuven(鲁汶大学);King’s College London(伦敦国王学院)

Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir, Jan Deprest, Sebastien Ourselin, Juan Eugenio Iglesias, Tom Vercauteren

英文摘要:

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, fully automated registration of such long-range pairs is (i) challenging when the registration of images itself is difficult; and (ii) computationally expensive for long sequences due to the large number of candidate pairs for registration. In this paper, we introduce an efficient framework for the active annotation of long-range pairwise correspondences in a sequence. Our framework suggests pairs of images that are sought to be informative to an oracle agent (e.g., a human user, or a reliable matching algorithm) who provides visual correspondences on each suggested pair. Informative pairs are retrieved according to an iterative strategy based on a principled annotation reward coupled with two complementary and online adaptable models of frame overlap. In addition to the efficient construction of a mosaic, our framework provides, as a by-product, ground truth landmark correspondences which can be used for evaluation or learning purposes. We evaluate our approach in both automated and interactive scenarios via experiments on synthetic sequences, on a publicly available dataset for aerial imaging and on a clinical dataset for placenta mosaicking during fetal surgery.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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