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In this paper, we take up the long-standing problem of how to recover 3-D shapes represented by a 2-D image, such as the image on the retina of the eye, or in a video camera. Our approach is biologically grounded in a theory of how the human visual system solves this problem, focusing on shapes that are mirror symmetrical in 3-D. A 3-D mirror-symmetrical shape can be recovered from a single 2-D orthographic...
Human beings perceive 3D shapes veridically, but the underlying mechanisms remain unknown. The problem of producing veridical shape percepts is computationally difficult because the 3D shapes have to be recovered from 2D retinal images. This paper describes a new model, based on a regularization approach, that does this very well. It uses a new simplicity principle composed of four shape constraints:...
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