Mobile Robot Range Sensing through Visual Looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer I mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.Defense Advanced Research Projects Agency; Office of Naval Research; Navy Research Laboratory (00014-96-1-0772, 00014-95-1-0409

A Variational Approach to the Evolution of Radial Basis Functions for Image Segmentation

In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variational calculus to energy functionals designed for image segmentation. Our methodology supports evolution of all parameters of each RBF, including its position, weight, orientation, and anisotropy, if present. Our framework is general and can be applied to numerous RBF interpolants. The resulting approach retains some of the ideal features of implicit active contours, like topological adaptivity, while requiring low storage overhead due to the sparsity of our representation, which is an unstructured list of RBFs. We present the theory behind our technique and demonstrate its usefulness for image segmentation