Abstract
While the perception of an object from a single image is hard for machines, it is a much easier task for humans since humans often have prior knowledge about the underlying nature of the object. Considerable work has recently been done on the combination of human perception with machines’ computational capability to solve some ill-posed problems such as 3D reconstruction from single image. In this work we present SLOREV (Sweep-Loft-Revolve), a novel method for modeling 3D objects using 2D shape snapping and traditional computer-aided design techniques. The user assists recognition and reconstruction by choosing, drawing and placing specific 2D shapes. The machine then snaps the shapes to the automatically detected contour lines, calculates their orientations in 3D space, and constructs the original 3D objects following classical CAD methods.
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Hu, P., Cai, H., Bu, F. (2015). SLOREV: Using Classical CAD Techniques for 3D Object Extraction from Single Photo. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds) MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science, vol 8936. Springer, Cham. https://doi.org/10.1007/978-3-319-14442-9_54
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DOI: https://doi.org/10.1007/978-3-319-14442-9_54
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