Extending 2-D Smoothed Local Symmetries to 3-D

3-D Smoothed Local Symmetries (3-D SLS's) are presented as a representation for three-dimensional shapes. 3-D SLS's make explicit the perceptually salient features of 3-D objects and are especially suited to representing man-made objects. The definition of the 3-D SLS is given as a natural extension of the 2-D Smoothed Local Symmetry (2-D SLS). Analytic descriptions of the 3-D SLS are derived for objects composed of planar and spherical patches. Results of an implementation of the 3-D SLS are presented, along with suggestions for further research.MIT Artificial Intelligence Laborator

The GSL Cookbook

This cookbook contains recipes prepared for the GSL (Graduate Student Lunch) at the Massachusetts Institute of Technology Artificial Intelligence Laboratory.MIT Artificial Intelligence Laborator

Stereo Feature Matching in Disparity Space

This paper describes a new method for matching, validating, and disambiguating features for stereo vision. It is based on the Marr-Poggio- Grimson stereo matching algorithm which uses zero-crossing contours in difference-of-Gaussian filtered images as features. The matched contours are represented in disparity space, which makes the information needed for matched contour validation and disambiguation easily accessible. The use of disparity space also makes the algorithm conceptually cleaner than previous implementations of the Marr-Poggio-Grimson algorithm and yields a more efficient matching process

Location Recognition Using Stereo Vision

A mobile robot must be able to determine its own position in the world. To support truly autonomous navigation, we present a system that builds and maintains its own models of world locations and uses these models to recognize its world position from stereo vision input. The system is designed to be robust with respect to input errors and to respond to a gradually changing world by updating the world location models. We present results from tests of the system that demonstrate its reliability. The model builder and recognition system fit into a planned world modeling system that we describe

An Alternative to Using the 3D Delaunay Tessellation for Representing Freespace

Representing the world in terms of visible surfaces and the freespacesexisting between these surfaces and the viewer is an important problemsin robotics. Recently, researchers have proposed using the 3DsDelaunay Tessellation for representing 3D stereo vision data and thesfreespace determined therefrom. We discuss problems with using thes3D Delaunay Tessellation as the basis of the representation andspropose an alternative representation that we are currentlysinvestigating. This new representation is appropriate for planningsmobile robot navigation and promises to be robust when using stereosdata that has errors and uncertainty