In this paper we present a new and simple method for fitting a sphere-like surface to a set of data points in 3-space. In comparison to the standard method that involves using spherical harmonics, this method is conceptually simpler and computationally less complex and intensive, especially when used to address problems in which data is sparse or nonuniform.

In this paper we present several models for solving map building and navigation problems. These models are motivated by biological processes, and presented in the context of artificial neural networks. Since the nodes, weights, and threshold functions of our models all have physical meanings, we can easily predict network topologies and avoid traditional trial-and-error training. On one hand, this makes our models useful in constructing solutions to engineering problems (problems such as those that occur in robotics, for example). On the other hand, this might also contribute to the ability of our models to explain some biological processes, few of which are completely understood at this time.>

The author presents a quick and easy solution to the camera calibration problem of finding the scale factor that arises because of a difference between the scanning frequency of the camera sensor plane and the scanning frequency of the image capture board frame buffer. The method presented is based on the observation that the scale factor is related to the distortion in an image of a circle: this is a distortion that can easily be measured by considering the occluding boundary of a precisely fabricated sphere, such as a ball bearing. Implementation results are presented.>

A shape-from-shading analysis for a single perspective image of a polyhedron is presented. Given a single perspective image of a polyhedron, the depth of any point of the polyhedron from the camera, the direction of the light source illuminating the polyhedron and the albedo of the polyhedron, a system of algebraic equations are derived, which, when combined with edge information, quantitatively describes the shape of the polyhedron. This analysis is best possible in the sense that if any component of what the author has assumed is omitted, no similar analysis can provide the same results.>