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    Analysis, reconstruction and manipulation using arterial snakes

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    Type
    Conference Paper
    Authors
    Li, Guo
    Liu, Ligang
    Zheng, Hanlin
    Mitra, Niloy J. cc
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Visual Computing Center (VCC)
    Date
    2010
    Permanent link to this record
    http://hdl.handle.net/10754/575746
    
    Metadata
    Show full item record
    Abstract
    Man-made objects often consist of detailed and interleaving structures, which are created using cane, coils, metal wires, rods, etc. The delicate structures, although manufactured using simple procedures, are challenging to scan and reconstruct. We observe that such structures are inherently 1D, and hence are naturally represented using an arrangement of generating curves. We refer to the resultant surfaces as arterial surfaces. In this paper we approach for analyzing, reconstructing, and manipulating such arterial surfaces. The core of the algorithm is a novel deformable model, called arterial snake, that simultaneously captures the topology and geometry of the arterial objects. The recovered snakes produce a natural decomposition of the raw scans, with the decomposed parts often capturing meaningful object sections. We demonstrate the robustness of our algorithm on a variety of arterial objects corrupted with noise, outliers, and with large parts missing. We present a range of applications including reconstruction, topology repairing, and manipulation of arterial surfaces by directly controlling the underlying curve network and the associated sectional profiles, which are otherwise challenging to perform. © 2010 ACM.
    Sponsors
    We thank the anonymous reviewers for their constructive comments. Several people helped in generating comparison results for Figure 11 namely Junjie Cao and Oscar Au for Laplacian contraction, Misha Kazhdan for Poisson surface reconstruction, Balint Miklos for scale axis computation, Cengiz Oztireli for kernel-regression reconstruction, Andrea Tagliasacchi and Richard Hao Zhang for curve skeleton computation, and Guanghua Tan for MPU reconstruction. We thank Min Yue for her help in obtaining the physical models scanned for this paper, Martin Peternell and Johannes Wallner for their help with scanning the models, and Jonathan Balzer for video narration. Ligang Liu is supported by the 973 National Key Basic Research Foundation of China (No. 2009CB320801) and the joint grant of the National Natural Science Foundation of China and Microsoft Research Asia (No. 60776799). Niloy Mitra was partially supported by a Microsoft outstanding young faculty fellowship.
    Publisher
    Association for Computing Machinery (ACM)
    Journal
    ACM SIGGRAPH Asia 2010 papers on - SIGGRAPH ASIA '10
    Conference/Event name
    ACM SIGGRAPH Asia 2010, SIGGRAPH Asia 2010
    ISBN
    9781450304399
    DOI
    10.1145/1866158.1866178
    10.1145/1882261.1866178
    ae974a485f413a2113503eed53cd6c53
    10.1145/1866158.1866178
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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