Abstract: In computer vision, chirality refers to the constraint that for a scene to be visible in a camera, it must lie in front of the camera. Ignoring this important physical constraint there is now a mature algebraic theory of image formation in pinhole cameras. In this talk I will discuss new structural results that arise from respecting chirality. Using real and semialgebraic geometry one can explicitly describe the set of all true images in an arrangement of cameras. The converse question is when given tuples of points are indeed the images of world points in front of cameras. I will give a complete answer in the case of two cameras, uncovering an unexpected connection to the classical theory of cubic surfaces with 27 real lines
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