In edge and corner detection applications, it is typical to examine a single scale without knowing which scale is appropriate for each location in the image. However, many images contain a wide variation in the distance to the scene pixels and, thus, features of the same size can appear at greatly differing scales in the image. We present a method where the scale of the filtering and feature detection is varied locally according to the distance to the scene pixel, which we estimate through stereoscopy. The features that are detected are, thus, at the same scale in the world, rather than at the same scale in the image. This method has been implemented efficiently by filtering the image at a discrete set of scales and performing interpolation to estimate the response at the correct scale for each pixel. The application of this technique to an ordnance recognition problem has resulted in a considerable improvement in performance.
['Clark F. Olson']
Adaptive-scale filtering and feature detection using range data