The digital Michelangelo project: 3D scanning of large statues

By Marc Levoy, Kari A. Pulli, Brian Curless, Szymon Rusinkiewicz, David Koller, L. Pereira, Matt Ginzton, Sean E. Anderson, James Davis, Jeremy Ginsberg and 2 more. 2000

1,861 citations recorded by the source corpus.

We describe a hardware and software system for digitizing the shape and color of large fragile objects under non-laboratory conditions. Our system employs laser triangulation rangefinders, laser time-of-flight rangefinders, digital still cameras, and a suite of software for acquiring, aligning, merging, and viewing scanned data. As a demonstration of this system, we digitized 10 statues by Michelangelo, including the well-known figure of David, two building interiors, and all 1,163 extant fragments of the Forma Urbis Romae, a giant marble map of ancient Rome. Our largest single dataset is of the David - 2 billion polygons and 7,000 color images. In this paper, we discuss the challenges we faced in building this system, the solutions we employed, and the lessons we learned. We focus in particular on the unusual design of our laser triangulation scanner and on the algorithms and software we developed for handling very large scanned models.

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Citations in the corpus

Efficient simplification of point-sampled surfaces (2002, background): “For surface data acquisition, modern 3D scanning devices are capable of producing point sets that contain millions of sample points [18].”
Unstructured lumigraph rendering (2001, unknown): “This limits the applicability of this method since it requires a special capture gantry that is both expensive and difﬁcult to use in many settings [11].”
Heritage Recording and 3D Modeling with Photogrammetry and 3D Scanning (2011, background): “realized very good quality and complete digital models [3-9].”
Geometrically stable sampling for the ICP algorithm (2003, methodology): “Figure 9(a) shows the sampling of two scans from the Forma Urbis Romae dataset [7].”
Manipulator and object tracking for in-hand 3D object modeling (2011, background): “, 2001) and can recover amazing details by combining elaborate hardware with meticulous experimental setup, such as that in the Digital Michelangelo Project (Levoy et al., 2000).”
A survey of point-based techniques in computer graphics (2004, methodology): “The steadily increasing performance of CPUs and graphics hardware, the cheap memory, and the wide availability of range-scanning devices result in the acquisition and generation of massive highly detailed geometry data — models consisting of several millions of triangles are common nowadays ( Levoy ”
Articulated mesh animation from multi-view silhouettes (2008, methodology): “The template mesh may be obtained by various means, such as 3D scanning [Levoy et al. 2000], static multi-view stereo of a single frame [Seitz et al.”
Point set surfaces (2001, background): “One reason for this is the emergence of affordable and accurate scanning devices generating a dense point set, which is an initial representation of the physical model [28].”