This paper proposes a novel approach, the sinogram polygonizer, for directly reconstructing 3D shapes from sinograms (i.e., the primary output from X-ray computed tomography (CT) scanners consisting of projection image sequences of an object shown from different viewing angles). To obtain a polygon mesh approximating the surface of a scanned object, a grid-based isosurface polygonizer, such as Marching Cubes, has been conventionally applied to the CT volume reconstructed from a sinogram. In contrast, the proposed method treats CT values as a continuous function and directly extracts a triangle mesh based on tetrahedral mesh deformation. This deformation involves quadratic error metric minimization and optimal Delaunay triangulation for the generation of accurate, high-quality meshes. Thanks to the analytical gradient estimation of CT values, sharp features are well approximated, even though the generated mesh is very coarse. Moreover, this approach eliminates aliasing artifacts on triangle meshes.

When creating a physical model to 3D print, the density distribution of an object is important because it determines the mass properties of objects such as center of mass, total mass and moment of inertia. In this paper, we present a density aware shape modelling method to control the mass properties of 3D printed objects. We generate a continuous density distribution that satisfies the given mass properties and generate a 3D printable model that represents this density distribution using a truss structure. The number of nodes and their positions are iteratively optimized so as to minimize error between the target density and the density of the truss structure. With our technique, 3D printed objects that have desired mass properties can be fabricated.

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We propose a novel painting interface that enables users to design an illumination distribution for a real room using an array of computer-controlled lights. Users specify which area of the room is to be well-lit and which is to be dark by painting a target illumination distribution on a tablet device displaying the image obtained by a camera mounted in the room. The painting result is overlaid on the camera image as contour lines of the target illumination intensity. The system then runs an optimization to calculate light parameters to deliver the requested illumination condition. We implemented a GPU-based parallel search to M. Inami Keio University,Tokyo, Japan achieve real-time processing. In our system, we used actuated lights that can change the lighting direction to generate the requested illumination condition more faithfully than static lights. We built a miniature-scale experimental environment and ran a user study to compare our method with a standard direct manipulation method using sliders. The results showed that the users preferred our method for informal light control.

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