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CurveFusion: Reconstructing Thin Structures from RGBD Sequences

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arxiv 2107.05284 v1 pith:4NMAMX6V submitted 2021-07-12 cs.GR

CurveFusion: Reconstructing Thin Structures from RGBD Sequences

classification cs.GR
keywords thincurvefusionskeletonstructurescurvergbdsequencesbundles
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We introduce CurveFusion, the first approach for high quality scanning of thin structures at interactive rates using a handheld RGBD camera. Thin filament-like structures are mathematically just 1D curves embedded in R^3, and integration-based reconstruction works best when depth sequences (from the thin structure parts) are fused using the object's (unknown) curve skeleton. Thus, using the complementary but noisy color and depth channels, CurveFusion first automatically identifies point samples on potential thin structures and groups them into bundles, each being a group of a fixed number of aligned consecutive frames. Then, the algorithm extracts per-bundle skeleton curves using L1 axes, and aligns and iteratively merges the L1 segments from all the bundles to form the final complete curve skeleton. Thus, unlike previous methods, reconstruction happens via integration along a data-dependent fusion primitive, i.e., the extracted curve skeleton. We extensively evaluate CurveFusion on a range of challenging examples, different scanner and calibration settings, and present high fidelity thin structure reconstructions previously just not possible from raw RGBD sequences.

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