Locating Known Objects In 3-D From A Single Perspective View

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Abstract
Determining the 3-D location of an object from image-derived features, such as edges and vertices, has been a central problem for the computer vision industry since its inception. This paper reports on the use of four coplanar points (in particular, a rectangle) and three points for determining 3-D object position from a single perspective view. The four-point algorithm of Hung and Yeh is compared to the four-point algorithm of Haralick. Both methods uniquely solve the inverse perspective problem, but in different ways. The use of three points has proven to be more difficult, mainly because of multiple solutions to the inverse perspective problem as pointed out by Fischler and Bolles. This paper also presents computer simulation results that demonstrate the spatial constraints associated with these multiple solutions. These results provide the basis for discarding spurious solutions when some prior knowledge of configuration is available. Finally, the use of vertex-pairs introduced by Thompson and Mundy is analyzed and compared to the other method.

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