A 3D Shape Descriptor for Segmentation of Unstructured Meshes into Segment-Wise Coherent Mesh Series

Mukasa, Tomoyuki; Nobuhara, Shohei; Tung, Tony; Matsuyama, Takashi

doi:10.1109/3dv.2014.20

Cited by 1 publication

(1 citation statement)

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“…[19]. This article enhances the method with an improved tips correspondence detection (Section 3.1.2), surface segmentation (Section 3.2) and detailed evaluations including kinematic structure estimation using newly-captured non-human dataset (Section 4).…”

Section: Introductionmentioning

confidence: 99%

Part-wise Geodesic Histogram Shape Descriptor for Unstructured Mesh Series Segmentation

Mukasa

Nobuhara

Tung

et al. 2016

IPSJ Transactions on Computer Vision and Applications

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This paper presents a novel shape descriptor for topology-based segmentation of 3D video sequences. 3D video is a series of 3D meshes without temporal correspondences which benefit for applications including compression, motion analysis, and kinematic editing. In 3D video, both 3D mesh connectivities and the global surface topology can change frame by frame. This characteristic prevents from making accurate temporal correspondences through the entire 3D mesh series. To overcome this difficulty, we propose a two-step strategy which decomposes the entire sequence into a series of topologically coherent segments using our new shape descriptor, and then estimates temporal correspondences on a per-segment basis. As the result of acquiring temporal correspondences, we could extract rigid parts from the preprocessed 3D video segments to establish partial kinematic structures, and could integrate them into a single unified kinematic model which describes the entire kinematic motion in the 3D video sequence. We demonstrate the robustness and accuracy of the shape descriptor on real data which consist of large non-rigid motion and reconstruction errors.

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Section: Introductionmentioning

confidence: 99%