STEREO RECONSTRUCTION FROM MULTIPERSPECTIVE PANORAMAS

Patent №

US 6,639,596

Granted

2003-10-28

Filed 1999

Owner

MICROSOFT CORPORATION

AI components

1

vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09399426

A system and process for computing a 3D reconstruction of a scene using multiperspective panoramas. The reconstruction can be generated using a cylindrical sweeping approach, or under some conditions, traditional stereo matching algorithms. The cylindrical sweeping process involves projecting each pixel of the multiperspective panoramas onto each of a series of cylindrical surfaces of progressively increasing radii. For each pixel location on each cylindrical surface, a fitness metric is computed for all the pixels projected thereon to provide an indication of how closely a prescribed characteristic of the projected pixels matches. Then, for each respective group of corresponding pixel locations of the cylindrical surfaces, it is determined which location has a fitness metric that indicates the prescribed characteristic of the projected pixels matches more closely than the rest. For each of these winning pixel locations, its panoramic coordinates are designated as the position of the portion of the scene depicted by the pixels projected to that location. Additionally, in some cases a sufficiently horizontal epipolar geometry exists between multiperspective panoramas such that traditional stereo matching algorithms can be employed for the reconstruction. A symmetric pair of multiperspectives panoramas produces the horizontal epipolar geometry. In addition, this geometry is obtained if the distance from the center of rotation to the viewpoints used to capture the images employed to construct the panorama is small in comparison to the distance from the center of rotation to the nearest scene point depicted in the images, or if an off-axis angle is kept small.

VisionG06T 3/4038G06T 7/30G06T 7/593G06V 10/147G06V 2201/12

AI classification

Vision1.00
AI hardware0.00
Knowledge representation0.00
Evolutionary computation0.00
Natural language0.00
Planning0.00
Machine learning0.00
Speech0.00

Ownership

MICROSOFT CORPORATION

assignment · 103930604

Assignors

SHUM, HEUNG-YEUNG, SZELISKI, RICHARD S.

On an employer assignment, the assignors are typically the inventors.

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