Apple Inc.

Shuang Gao

Emilie Kim

Robert A Bailey

Yang Yang

Xiaosong Zhou

Rudolph Van Der Merwe

Vignesh Jagadeesh

Jason Klivington

Ke Zhang

Jacques P Gasselin De Richebourg

Alexandre Naaman

Vinay Sharma

Piotr J Stanczyk

Richard David Seely

Patrick Shehane

Afshin Dehghan

Arwen V Bradley

Paul Thomas Schneider

Bartlomiej W Rymkowski

Shujie Liu

Ethan J Tira-Thompson

Vasilios E Anton

Joe Triscari

Ben Englert

Sébastien Beysserie

Techniques disclosed for managing video captured by an imaging device. Methods disclosed capture a video in response to a capture command received at the imaging device. Following a video capture, techniques for classifying the captured video based on feature(s) extracted therefrom, for marking the captured video based on the classification, and for generating a media item from the captured video according to the marking are disclosed. Accordingly, the captured video may be classified as representing a static event, and, as a result, a media item of a still image may be generated. Otherwise, the captured video may be classified as representing a dynamic event, and, as a result, a media item of a video may be generated.

Automated media editing operations in consumer devices

Techniques are disclosed for editing captured media to overcome operational difficulties that may arise during capture operations. According to these techniques, content may be captured with a pair of cameras, a first camera having a wider field of view than a second camera. Object(s) may be detected from captured content from the wider field of view camera. The captured content may be processed from the wider field of view camera in a location of at least one detected object. Typically, operators may attempt to frame content using content from the narrower field of view camera. As a result, operators may be unaware that desired content is captured using a second, wider field of view camera. Results from the processed wider field of view data may be proposed to operators for review and, if desired, retention.

Video analysis and management techniques for media capture and retention

This disclosure relates to techniques for synthesizing out of focus blurring effects in digital images. Cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). SDOF cameras are often used in portrait photography, since they emphasize subjects, while deemphasizing the background via blurring. Simulating this kind of blurring using a large depth of field (LDOF) camera may require a large amount of computational resources, i.e., to simulate the physical effects of using a wide aperture lens, while constructing a synthetic SDOF image. Moreover, cameras having smaller lens apertures, such as those in mobile phones, may not have the ability to accurately estimate or recreate the true color of clipped background light sources. Described herein are techniques to synthesize out of focus background blurring effects that attempt to reproduce accurate light intensity and color values for clipped background light sources in images captured by LDOF cameras.

Highlight recovery techniques for shallow depth of field rendering

Growing community of inventors

Cupertino, CA, United States of America

Shuang Gao