A scale adaptive method for estimating the perspective pose of texture planes

Multiple vanishing point detection provides the key to recovering the perspective pose of textured planes. If vanishing points are to be detected from spectral information then there are two computational problems that need to be solved. Firstly, the search of the extended image plane is unbounded, and hence the location of vanishing points at or near infinity is difficult. Secondly, correspondences between local spectra need to be established so that vanishing points can be triangulated. In this paper, we offer a way of overcoming these two difficulties. We overcome the unbounded search problem by mapping the information provided by local spectral moments onto the unit sphere. According to our representation, the position and direction of each local spectrum maps onto a great circle on the unit sphere. The need for correspondences is overcome by accumulating the great-circle intercepts. Vanishing points occur at local accumulator maxima on the unit sphere. To improve the accuracy of the recovered perspective pose parameters for highly slanted planes, we use an adaptive spectral window. This selects the window so as to reduce spectral defocusing by minimising the determinant of the spectral covariance matrix. We experiment with the new shape-from-texture technique on both synthetic and real-world data; it proves to be an accurate and robust means of estimating perspective pose.