Title :
Adapting scale by minimising spectral defocusing for shape from texture
Author :
Ribiero, E. ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
Abstract :
Spectral analysis provides a powerful means of estimating the perspective pose of texture planes. Unfortunately one of the problems that restricts the utility of the method is the need to set the size of the spectral window. For texture planes viewed under extreme perspective distortion, the spectral frequency density may vary rapidly across the image plane. If the size of the window is mismatched to the underlying texture distribution, then the estimated frequency spectrum may become severely defocused. This in turn limits the accuracy of perspective pose estimation. The aim in this paper is to describe an adaptive method for setting the size of the spectral window. We provide an analysis which shows that there is a window size that minimises the degree of defocusing
Keywords :
adaptive signal processing; image texture; minimisation; spectral analysis; adaptive method; image plane; perspective distortion; perspective pose; shape; shape from texture; spectral analysis; spectral defocusing; spectral frequency density; spectral window; texture planes; Adaptive filters; Computer science; Covariance matrix; Frequency estimation; Image edge detection; Merging; Optimized production technology; Shape; Spectral analysis; Spectrogram;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.899600