Google Inc.

Jason Chang

Teresa Ko

Loren Puchalla Fiore

Catherine Wah

Shengyang Dai

David Foster Lieb

Jingyu Cui

James A Gallagher

Kedar Kanitkar

Taehee Lee

Nan Wang

Dominick Lim

Kristi Bohl

Vidya Valmikinathan

Jeremy Zhu

Aravind Krishnaswamy

Daniel Pettigrew

Sevket Derin Babacan

Ronald Frank Wotzlaw

Zhen Li

Futang Peng

Lily Berg

Kristina Bohl

David William Hendon

Ivan Oropeza

Ethan Schreiber

Tracy Gu

Howard Zhou

Shanfeng Zhang

A media application determines, based on pixels of images or videos from a collection of media items, clusters of media items such that the media items in each cluster have a visual similarity, wherein the collection of media items is associated with a user account. The media application selects a subset of the clusters of media from corresponding clusters of media items based on the media items in each cluster having a visual similarity within a range of threshold similarity values. The media application causes a user interface to be displayed that includes the subset of the clusters of media.

Determining a visual theme in a collection of media items

Implementations described herein relate to methods, devices, and computer-readable media to generate and provide image-based creations. A computer-implemented method includes obtaining a plurality of episodes, each episode associated with a corresponding time period and including a respective set of images and person identifiers for each image. The method further includes forming a respective cluster for each episode that includes at least two person identifiers. The method further includes determining whether one or more person identifiers are included in less than a threshold number of clusters, and in response, removing the one or more person identifiers from the clusters that the one or more person identifiers that are included in. The method further includes merging identical clusters to obtain a plurality of people groups that each include two or more person identifiers and providing a user interface that includes an image-based creation based on a particular people group.

Automatic generation of people groups and image-based creations

Implementations relate to sharing images and image albums over a communication network. In some implementations, a computer-implemented method includes determining that a shared album data structure is accessible by a device and includes references to album images. The device determines one or more suggested images from a collection of stored images associated with a user, based on determining sharing scores for the stored images. The sharing scores are based on comparing one or more characteristics of the stored images to one or more corresponding characteristics of the album images. The method includes causing display of the one or more suggested images by the device, receiving a selection of at least one selected image of the suggested images based on received user input, and causing an update of the shared album data structure with the at least one selected image to be accessible over a communication network by recipient users.

Sharing images and image albums over a communication network

Some implementations can include a computer-implemented method and/or system for automatic suggestion to share images. The method can include identifying a plurality of images associated with a user and detecting one or more entities in the plurality of images. The method can also include constructing an aggregate feature vector for the plurality of images based on the one or more entities in the plurality of images and determining that the aggregate feature vector matches a first cluster. The method can further include, in response to determining that the aggregate feature vector matches the first cluster, providing a suggestion to the user for an image composition based on the plurality of images.

Automatic suggestion to share images

Some implementations can include a computer-implemented method and/or system for automatic suggestions to share images containing people of importance to a user. The method can include determining, based on pixels of an image associated with a user account, one or more clusters associated with the image. The method can also include determining a share probability score for the image based on a probabilistic model and determining that the share probability score meets a threshold. The method can further include, in response to determining that the share probability score meets the threshold, providing a suggestion to a user associated with the user account to share the image.

Automatic suggestions to share images

Methods and systems for modifying an image by applying an effect to an image are described. The effects include a pop effect, a light adjustment, or a color adjustment to an image. The methods and systems include providing a user slider for applying an effect to the image. The methods and systems further include determining a first portion of the image including a face and creating a protection mask to protect the face in the first portion during image modification. The protection mask may include an enhancement threshold for modifying the first portion of the image. The modification of the image may include modifying the second portion of the image differently than the first portion of the image. A method for enforcing different resolutions of a same input image to produce similar visual results is also described.

User sliders for simplified adjustment of images

Implementations relate to image feature detection and masking in images based on color distributions. In some implementations, a computer-implemented method to determine a mask for an image includes determining a spatial function for a detected feature depicted in the image, the function indicating pixels of the image relative to an estimated feature boundary. A respective color likelihood distribution is determined for each of multiple regions of the image based on one or more distributions of color values in the regions, including a feature region and a non-feature region. A confidence mask is determined based on the spatial function and one or more of the color likelihood distributions. The confidence mask indicates, for each of multiple pixels of the image, an associated confidence that the pixel is a feature pixel. A modification is applied to pixels in the image using the confidence mask.

Feature detection and masking in images based on color distributions

A system for dynamic collage layout generation comprises a processor and a memory storing instructions that, when executed, cause the system to: receive a plurality of pictures to arrange into a collage, calculate pairwise distances between the plurality of pictures, arrange the plurality of pictures into one or more groups based on the pairwise distances between the plurality of pictures, calculate a group arrangement cost based on an aspect ratio of the one or more groups, determine an arrangement of the one or more groups based on the group arrangement cost, and place the pictures in a collage layout based on the arrangement of the one or more groups. The disclosure also includes similar methods and computer program products.

Dynamic collage layout generation

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Mountain View, CA, United States of America

Jason Chang