Microsoft Technology Licensing, LLC

David Benjamin Lee

Allison Light

Chunkit Jacky Chan

Ilya Tumanov

Nathaniel George Freier

Christopher Hugh Pratley

Brett David Brewer

Sarah Faulkner

Katrika Marie Morris

Jennifer P Michelstein

Jennifer Michelstein Halberstam

Steven Richard Hollasch

Stacia Scott

Doug Ricard

Nathan George Freier

Erez Kikin Gil

Erez Kikin-Gil

Nino Yuniardi

Karim Taji Farouki

Kuldeep Karnawat

Joseph Freeman Friend

Jeffrey Scott Berg

Derek Matthias Hans

Joo Young Lee

Catalin Alexandru Negrila

John Gabriel D'Angelo

Daniel Cory

Mark James McNulty

Hai Liu

Zeyad Rajabi

Suzan Marashi

Christopher Andrews Jung

Nathan James Fish

Seth Fox

Ian Dwyer Curry

Benjamin L Chronister

Dragan Slaveski

Dean Rowe

Chad Garrett Waldman

Anav Silverman

Martin Harm Hall

Robert Earl Stout

Kathryn Veronica Jean Sullivan

Bradley W Ward

Stephanie Sharp

Nathan James Luquetta-Fish

Dimitrije Dimic

Technologies for grouping images, and ranking the images and the groupings, based on entities shown in the images. Images may be grouped based on faces shown in the images. Different images with faces that indicate the same entity (e.g., Adam) may be automatically grouped together. Different images with faces that indicate the same multiple entities (e.g., the people in my family) may also be automatically grouped together. Such automatic grouping may be based on facial recognition technologies. Further, images and groups of images may be automatically ranked based on the faces shown and entities represented. Such rankings may also be influenced by adjacent data that indicates family and friends and the like, and that can be used to identify such entities in the images.

Image scoring and identification based on facial feature descriptors

In various implementations, a productivity application allows selected content from an electronic document to be shared with and edited by multiple users through instances of a collaboration component. The collaboration component includes a distributed data structure that stores state information about the shared content. The component also includes application logic for managing the state information to reflect user edits and other such changes. This allows the selected content to be shared with the users in any application that supports the collaboration component and without the entirety of the document having to be shared. A user can experience the content in the context of applications other than the productivity application that hosts the document.

Collaboration components for sharing content from electronic documents

A UI for presenting and reviewing a document is optimized based upon the type of computing device being utilized to present the document. One such UI includes a first pane showing a view of the document under review that is sized and formatted for display on a large-format display device. The first pane can also be utilized to emphasize a portion of the document. The UI also includes a second pane that includes indicators for each of the reviewers of the document. The selection of an indicator will cause a portion of the document being reviewed by the corresponding reviewer to be displayed in the first pane. The UI also includes a third pane that includes a scaled image of the document shown in the first pane. Selection of a portion of the scaled image causes the selected portion of the document to be displayed in the first pane.

Optimized joint document review

Technologies for analyzing various features detected in a face detected in an image. Such features may include at least the eyes, eyebrows, node, and mouth of a face. Such analyzing may include scoring aspects of these features. Such scores may be weighted. The analysis may be used to determine expressions and/or poses of the face, as well as indicate if the face is smiling, frowning, or neutral. An overall quality score for the face may also be determined and provided based on the aforementioned analysis as well as whether or not the face is near an edge of the image or cut-off in the image. Finally, a face signature may be determined that uniquely identifies the face, at least within the scope of the analyzed features. Such face signatures may be used to detect a similar face in other images.

Creation of representative content based on facial analysis

Concepts and technologies are described herein for transforming data to create layouts. In accordance with the concepts and technologies disclosed herein, a computing device can execute a layout generator. The computing device can be configured to receive or retrieve data that includes visual content such as an image and other content such as text. The computing device can analyze the visual content to identify a salient region and/or an invariant region within the visual content. The computing device can access designs for laying out visual content and other content based upon an identified salient region and/or invariant region. The computing device can evaluate the designs to determine if a design matches the data. The computing device can load the data into the selected design to generate the layout.

Transforming data to create layouts

Disclosed in some examples are methods, systems, computing devices, and machine readable mediums that provide for cropping systems that automatically crop digital images using one or more smart cropping techniques. Smart cropping techniques may include: cropping an image based upon emotion detection, cropping based upon facial recognition and matching, and cropping based upon landmark matching. In some examples, a single smart cropping technique may be utilized. In other examples, a combination of the smart cropping techniques may be utilized.

Intelligent auto cropping of digital images

Grouping and ranking images based on facial recognition data

Non-limiting examples of the present disclosure describe automatic creation of a composite data object from a received drag and drop action. A drag and drop action is received through a user interface of a productivity service. The drag and drop action is analyzed, where an analysis comprises: evaluation of attributes of data objects of the drag and drop action, evaluation of a relationship between the data objects and a determination of user intent for the drag and drop action based on a placement of the first data object onto a position of the second data object. A group type is created that comprises an arrangement of the first data object and the second data object based on the analysis of the drag and drop action. A representation of a composite data object is surfaced, through the user interface, based on the created group type.

Drag and drop of objects to create new composites

Improved computer efficiency for document navigation is provided. A transparent overlay is automatically applied to an interactive content element to prevent inadvertent interaction with the element during scrolling operations. In some examples, upon determining a user's intent is to navigate a parent document comprising an embedded interactive element, the overlay is applied, and user-interaction with the interactive element is temporarily disabled. Upon determining the user's intent is to interact with the interactive element, the overlay is removed, and user-interaction with the interactive element is enabled. When the overlay is removed, a contextual hint, such as via a user interface control, can be provided to indicate how to continue navigating the parent document. In other examples, the transparent overlay is customized according to each interactive content element, wherein user controls associated with the interactive element are exposed, and wherein the overlay is perpetually applied to the interactive element.

Intuitive document navigation with interactive content elements

Disclosed embodiments generally relate to logically describing and modeling the layout of an output (e.g., a document or a presentation) by capturing author intent. Author intent can be captured based on the author's selection of visual exemplars (e.g., lists, grids, collages, etc.) with which to express content. Each visual exemplar identifies one or more semantic expressions (e.g., specific, often implied, relationships that are represented in visual exemplars of content) that are represented by those visual exemplars. The identified semantic expressions form a contract that can be observed in any generated output. The output can be formatted and laid out in a variety of different ways (e.g., for a variety of different presentation devices) to provide aesthetic and semantic efficiency in the generated output while maintaining the intent of the author.

Output generation based on semantic expressions

Technologies for modifying a digital image to take on the appearance of an antique image. Such modifying is typically based on generating and rendering various effects that are blended with the input image, such as color transformation, simulating film grain, dust, fibers, tears, and vintage borders. Such effects may be rendered to various layers that are overlaid on a color transformed image resulting in what appears to be an antique image.

Saliency-preserving distinctive low-footprint photograph aging effects

Growing community of inventors

Sammamish, WA, United States of America

David Benjamin Lee