Apple Inc.

Zehang Sun

Randy Ubillos

Samuel Morgan Roberts

Timothy David Cherna

Toshihiro Horie

Xiaohuan Corina Wang

Brian Edward Walsh

Kevin M O'Neil

Greg Dudey

Stuart Mark Pomerantz

Nathalie Castel

Eric S Beale

Omid Khalili

Jean-Michel Berthoud

Andy Harding

Marc Robins

Joe Weil

Peter Chou

Xin Tong

Christopher R Cunningham

Some embodiments provide an image editing application that edits an image. The image editing application displays an image in a display area. The image editing application displays a rotatable user interface item. In response to receiving a user input, the image editing application rotates the rotatable user interface item. The image editing application rotates the image displayed in the display area based on the rotation of the rotatable user interface item.

User interface tools for cropping and straightening image

Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or 'AR selfies.' In an embodiment, a method comprises: capturing, by a first camera of a mobile device, live image data, the live image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Augmented reality self-portraits

Systems, methods, apparatuses and non-transitory, computer-readable storage mediums are disclosed for generating AR self-portraits or 'AR selfies.' In an embodiment, a method comprises: capturing, by a first camera of a mobile device, image data, the image data including an image of a subject in a physical, real-world environment; receiving, by a depth sensor of the mobile device, depth data indicating a distance of the subject from the camera in the physical, real-world environment; receiving, by one or more motion sensors of the mobile device, motion data indicating at least an orientation of the first camera in the physical, real-world environment; generating a virtual camera transform based on the motion data, the camera transform for determining an orientation of a virtual camera in a virtual environment; and generating a composite image data, using the image data, a matte and virtual background content selected based on the virtual camera orientation.

Creating augmented reality self-portraits using machine learning

In some implementations, a computing device can track an object from a first image frame to a second image frame using a self-correcting tracking method. The computing device can select points of interest in the first image frame. The computing device can track the selected points of interest from the first image frame to the second image frame using optical flow object tracking. The computing device can prune the matching pairs of points and generate a transform based on the remaining matching pairs to detect the selected object in the second image frame. The computing device can generate a tracking confidence metric based on a projection error for each point of interest tracked from the first frame to the second frame. The computing device can correct tracking errors by reacquiring the object when the tracking confidence metric is below a threshold value.

Long term object tracker

An efficient line detection technique pre-processes an image to remove edge pixels that are not on straight lines, before performing line detection. By removing edge pixels not on straight lines, the complexity of the task of line detection can be significantly reduced, while increasing the accuracy. Various embodiments preprocess the edge maps of an image by anisotropic line filtering, kernel density estimation-based edge pruning, and connected component analysis. The resulting pruned edge map may then be processed using a Hough transform to detect straight lines in the image, having removed much of the noise in the edge map.

Efficient line detection method

Growing community of inventors

Saratoga, CA, United States of America

Zehang Sun