2d-3d reasoning and augmented reality publications

A novel image-matching measure based on Minimum Description Length (MDL) theory allows us to estimate the accuracy of individual elements of the 3- D model. Experiments to demonstrate the utility…

We propose a methodology that estimates the accuracy and reliability of the results of any multiple-image point correspondence algorithm, without the need for ground truth or camera calibration.

A unified framework for 3-D shape reconstruction allows us to combine image-based and geometry-based information sources. The image information is akin to stereo and shape-from-shading, while the geometric information may…

The analysis side is the processing of sensory data for such tasks as recognition and navigation, and a number of techniques are discussed here for dealing with these two-, three-,…

An improved stochastic stereo-matching algorithm incorporates two substantial modifications to an earlier version: a new variation of simulated annealing.

This paper describes a new technique for use in the automatic production of digital terrain models from stereo pairs of aerial images.

A stochastic optimization approach to stereo matching is presented. The approach provides a dense array of disparities, eliminating the need for interpolation.

SRI International is implementing a complete, state-of the-art stereo system that will produce dense three-dimensional (3D) data from stereo pairs of intensity images.  This system forms a framework for much…

We are implementing a baseline system for automated area-based stereo compilation.

This report concentrates on textured-image segmentation using local texture-energy measures and user-delimited training regions. The SLICE algorithm combines knowledge of target textures or signatures with knowledge of background textures by…

A method for interpolating a surface through 3-D data is presented. The method is computationally efficient and general enough to allow the construction of surfaces with either smooth or rough…

A software evaluation methodology has been developed at SRI International for evaluating contributions to the ARPA/DMA Image Understanding Testbed. This paper describes the criteria that have shaped the evaluation methodology.