Adobe, Inc.

Gavin Miller

Byungmoon Kim

Joon-Young Lee

Jinwoong Jung

Tenell Glen Rhodes, Jr

Axel Schildan

Frank Jargstorff

Kevin Michael Goldsmith

The present disclosure includes methods and systems for modifying orientation of a spherical panorama digital image based on an inertial measurement device. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by detecting changes in orientation to an inertial measurement device and generating an enhanced spherical panorama digital image based on the detect changes. In particular, in one or more embodiments, the disclosed systems and methods modify orientation of a spherical panorama digital image in three-dimensional space based on changes in orientation to an inertial measurement device and resample pixels based on the modified orientation to generate an enhanced spherical panorama digital image.

Utilizing an inertial measurement device to adjust orientation of panorama digital images

The present disclosure includes methods and systems for correcting distortions in spherical panorama digital images. In particular, one or more embodiments of the disclosed systems and methods correct for tilt and/or roll in a digital camera utilized to capture a spherical panorama digital images by determining a corrected orientation and generating an enhanced spherical panorama digital image based on the corrected orientation. In particular, in one or more embodiments, the disclosed systems and methods identify line segments in a spherical panorama digital image, map the line segments to a three-dimensional space, generate great circles based on the identified line segments, and determine a corrected orientation based on the generated great circles.

Automatic orientation adjustment of spherical panorama digital images

Systems and techniques are disclosed that use an image capture device to capture images of an object under specified image capture conditions for use in determining reflectance properties of the object. Images of the object are captured from a variety of different camera directions and with the object illuminated from a variety of different light directions. To capture these images, a camera of the image capture device is moved relative to the object and lights of the device are selectively illuminated. The image capture device has various features that increase the variety and number of different image capture conditions that can be captured. For example, using planar arrays of individually addressable lights in the image capture device allows tens, hundreds, or even thousands of lights to be used. Using planar arrays of lights provides light from many different directions without adding substantial complexity or cost to the device.

Systems and techniques for capturing images for use in determining reflectance properties of physical objects

Various embodiments herein provide one or more systems, methods, software, and data structures for executing multiple functions using more than one resource within a computing system. Examples of functions comprise data processing filters and effects. Resources include, for example, a central processing unit (CPU) and a graphics processing unit (GPU). Based on an input graph received from a user, one or more execution graphs may be generated to indicate the resources to be used and data conversions to be performed.

System and method for executing multiple functions execution by generating multiple execution graphs using determined available resources, selecting one of the multiple execution graphs based on estimated cost and compiling the selected execution graph

A system that renders a three-dimensional model which contains semi-transparent surfaces. During operation, the system renders the semi-transparent surfaces in the three-dimensional model by performing the following operations iteratively for each semi-transparent surface in draw-order instead of depth-order: (1) rendering the semi-transparent surface to a Z buffer, (2) calculating a cumulative transparency value for each pixel of the semi transparent surface as a function of the transparency value for each opaque and semi-transparent surface that intersects the pixel and is in front of the Z-value for the pixel in the Z-buffer, (3) attenuating a surface color value for each pixel in the semi-transparent surface by the cumulative transparency value for the pixel, and (4) adding the attenuated surface color value to a corresponding pixel value in the image buffer.

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Los Altos, CA, United States of America

Gavin Miller