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Implicit representation and scene reconstruction from probability density functions

A technique is presented for representing linear features as probability density functions in two or three dimensions. Three chief advantages of this approach are (1) a unified representation and algebra for manipulating points, lines, and planes, (2) seamless incorporation of uncertainty information, and (3) a very simple recursive solution for maximum likelihood shape estimation. Applications to uncalibrated affine scene reconstruction are presented, with results on images of an outdoor environment.