Invariant Characterization of the Hough Transform forPose Estimation of Arbitrary Shapes
Alberto S. Aguado, E Montiel, Mark S. Nixon · 2000
The Hough transform extracts a shape by gathering evidence obtained by mapping points from the image space into a parameter space.In this process, wrong evidence is generated from image points that do not correspond to the model shape.In this paper, we show that significant wrong evidence can be generated when the Hough Transform is used to extract arbitrary shapes under rigid transformations.In order to reduce the wrong evidence, we consider two types of constraints.First, we define constraints by considering invariant features.Secondly, we consider constraints defined via a gradient direction information.Our results show that these constraints can significantly improve the gathering strategy, leading to identification of the correct parameters.The presented formulation is valid for any rigid transformations represented by affine mappings.