Google Inc.

Tingfang Du

Brendan Elwood Bevensee

Duane M Petrovich

Jie Tan

Thomas Nonn

Jon Karafin

Joel Merritt

Francois Bleibel

Gareth Spor

An image capture system includes a plurality of image sensors arranged in a pattern such that gaps exist between adjacent image sensors of the plurality of image sensors. Each of the image sensors may be configured to capture sensor image data. The image capture system may also have a main lens configured to direct incoming light along an optical path, a microlens array positioned within the optical path, and a plurality of tapered fiber optic bundles. Each tapered fiber optic bundle may have a leading end positioned within the optical path, and a trailing end positioned proximate one of the image sensors. The leading end may have a larger cross-sectional area than the trailing end. Sensor data from the image sensors may be combined to generate a single light-field image that is substantially unaffected by the gaps.

Video capture, processing, calibration, computational fiber artifact removal, and light-field pipeline

A depth-based effect may be applied to a multi-view video stream to generate a modified multi-view video stream. User input may designate a boundary between a foreground region and a background region, at a different depth from the foreground region, of a reference image of the video stream. Based on the user input, a reference mask may be generated to indicate the foreground region and the background region. The reference mask may be used to generate one or more other masks that indicate the foreground and background regions for one or more different images, from different frames and/or different views from the reference image. The reference mask and other mask(s) may be used to apply the effect to the multi-view video stream to generate the modified multi-view video stream.

Multi-view scene segmentation and propagation

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San Jose, CA, United States of America

Tingfang Du