Sparse3D: A new global model for matching sparse RGB-D dataset with small inter-frame overlap

Abstract We present a novel 3D global matching algorithm, Sparse3D, to handle the challenging reconstruction of RGB-D datasets whose inter-frame overlap is small due to insufficient temporal sampling or fast camera movement. To support a more reliable reconstruction, two major technical components are proposed: (1) pairwise alignment using a set of complementary features, and (2) a novel global model for alignment pruning and pose optimization. We examine the effectiveness of our algorithm on multiple benchmark datasets under various inter-frame overlap, and demonstrate it better reliability over existing RGB-D reconstruction algorithms.

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