Lucasfilm Entertainment Company Ltd.

Douglas Moore

Ronald Mallet

Paige M Warner

Patrick N P Conran

Jason Snell

Jeff Saltzman

Jason Billington

Jed Parsons

Arkell Rasiah

Tom Martinek

Dev Mannemela

System and methods are provided for a non-coherent point tracking process that allows unknown camera motion to be estimated. One or more edges can be identified in images captured by a camera when shooting a scene. For each of the identified edge in the images, at least one tracking object can be placed arbitrarily on the edge. The positions of tracking objects in the images can then be used to estimate a camera motion. In some embodiments, two tracking objects can be placed arbitrarily on the edge to represent the edge and move along the edge arbitrarily from image to image where the edge appears. Multiple of such edges can be identified in the images and camera motions in multiple directions can be estimated based on the identified edges and combined to obtain a combined camera motion indicating the camera's movement in a 3D space when shooting the scene.

Non-coherent point tracking and solving for ambiguous images and geometry

Methods and systems are disclosed for calibrating a camera using a calibration target apparatus that contains at least one fiducial marking on a planar surface. The set of all planar markings on the apparatus are distinguishable. Parameters of the camera are inferred from at least one image of the calibration target apparatus. In some embodiments, pixel coordinates of identified fiducial markings in an image are used with geometric knowledge of the apparatus to calculate camera parameters.

Automated camera calibration methods and systems

An apparatus is disclosed which may serve as a target for calibrating a camera. The apparatus comprises one or more planar surfaces. The apparatus includes at least one fiducial marking on a planar surface. The set of all planar markings on the apparatus are distinguishable.

Calibration target for video processing

In one aspect, a method is performed by one or more processors. The method includes receiving a primary view image showing a scene from a view of a primary camera; depth values for one or more objects in the scene; and a camera offset between the primary camera and a secondary camera. The method further includes determining disparities for each pixel in the primary view image. The method further includes generating a secondary view image using the primary view image, the depth values, and the camera offset. At least some of the pixels are repositioned according to the determined disparities.

Stereoscopic conversion

A computer-implemented method for configuring stereo cameras includes detecting, in a computer system, a relocation of a manipulator in a virtual set. The manipulator defined in the computer system to specify an aspect of the virtual set. The method includes receiving an input in the computer system, the input specifying an aspect of a projection environment. The method includes configuring, using the relocation and the input, first and second cameras to capture a stereo view of a scene such that the stereo view is compatible for being projected in the projection environment.

Configuring stereo cameras

A method performed by one or more processors includes: receiving model data defining a three-dimensional scene; rendering the three-dimensional scene into a primary view image showing the three-dimensional scene from a view of a primary camera; and generating, for each of at least some pixels in the primary view image, a disparity value that defines a disparity between a location of the pixel in the primary view image and an indicated location of the pixel in a secondary view image showing the three-dimensional scene from a view of a secondary camera.

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San Francisco, CA, United States of America

Douglas Moore