2d-3d reasoning and augmented reality publications

We examine the task of matching images of a scene when they are taken from very different vantage points, when there is considerable scale change, and when the image orientations…

This paper addresses the problems of: representing natural shapes such as mountains, trees, and clouds, and computing their description from image data.

The primary purpose of the Image Understanding (IU) Testbed is to provide a means for transferring technology from the DARPA-sponsored IU research program to DMA and other organizations in the…

In this paper we address a basic problem in machine perception: the tracing of "line-like" structures appearing in an image. It is shown that this problem can profitably be viewed…

This report summarizes applications for PHOENIX, the history and nature of the algorithm, details of the Testbed implementation, the manner in which it is invoked and controlled, the type of…

A new formulation of shape from shading is presented in which surface orientation is related to image irradiance without requiring detailed knowledge of the scene illumination, or of the albedo…

Local analysis of image shading, in the absence of prior knowledge about the viewed scene, may be used to provide information about the scene.

Two constructive methods are presented: the first finds the orientation of parallel lines and planes and the second determines the orientation of plans by `backprojection’ of two intrinsic properties of…

We broadly define computational stereo as the recovery of the three-dimensional characteristics of a scene from multiple images taken from different points of view.

We describe a solution for an important special case: the interpolation of surfaces that are locally spherical or cylindrical from initial orientation values and constraints on orientation.

In this paper a structural approach to modeling is argued for that explicitly relates image appearance to the scene characteristics from which it arose.

The importance of human vision is a major motivation for the intense interest in and significant research effort devoted to machine vision.