Abstract: Implementations of the present disclosure include actions of receiving image data, the image data being provided from a camera and corresponding to a scene viewed by the camera, receiving one or more annotations, the one or more annotations being provided based on one or more entities determined from the scene, each annotation being associated with at least one entity, determining one or more actions based on the one or more annotations, and providing instructions to display an action interface including one or more action elements, each action element being selectable to induce execution of a respective action, the action interface being displayed in a viewfinder.

Abstract: Systems and methods are provided for providing insight for entities in mobile onscreen content. For example, a method includes receiving, from a mobile device, an indication of selection of a first entity represented by a visual cue in first annotation data for a screen capture image of a screen of the mobile device and determining entities related to the first entity in a graph-based data store. The method may also include identifying a second entity in the screen capture image that is one of the entities related to the first entity, generating second annotation data, the second annotation data including a visual element linking the first entity and the second entity, and providing the second annotation data for display with the screen on the mobile device.

Abstract: Systems and methods prevent or restrict the mining of content on a mobile device. For example, a method may include identifying a mining-restriction mark in low order bits or high order bits in a frame buffer of a mobile device and determining whether the mining-restriction mark prevents mining of content. Mining includes non-transient storage of a copy or derivations of data in the frame buffer. The method may also include preventing the mining of data in the frame buffer when the mining-restriction mark prevents mining.

Abstract: Systems and methods are provided for a personal entity modeling for computing devices. For example, a computing device comprises at least one processor and memory storing instructions that, when executed by the at least one processor, cause the mobile device to perform operations including identifying a personal entity in content generated for display on the mobile device, generating training examples for the personal entity from the content, and updating an embedding used to model the personal entity using the training examples. The embedding may be used to make predictions regarding the personal entity. For example, the operations may also include predicting an association between a first personal entity displayed on the computing device and a second entity based on the embedding, and providing a recommendation, to be displayed on the computing device, related to the second entity.

Abstract: A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.

Abstract: Systems and methods are provided for a content-based security for computing devices. An example method includes identifying content rendered by a mobile application, the content being rendered during a session, generating feature vectors from the content and determining that the feature vectors do not match a classification model. The method also includes providing, in response to the determination that the feature vectors do not match the classification model, a challenge configured to authenticate a user of the mobile device. Another example method includes determining a computing device is located at a trusted location, capturing information from a session, the information coming from content rendered by a mobile application during the session, generating feature vectors for the session, and repeating this until a training criteria is met. The method also includes training a classification model using the feature vectors and authenticating a user of the device using the trained classification model.

Abstract: Systems and methods are provided for suggesting actions for entities discovered in content on a mobile device. An example method can include running a mobile device emulator with a deep-link for a mobile application, determining a main entity for the deep link, mapping the main entity to the deep link, storing the mapping of the main entity to the deep link in a memory, and providing the mapping to a mobile device, the mapping enabling a user of the mobile device to select the deep link when the main entity is displayed on a screen of the mobile device. Another example method can include identifying at least one entity in content generated by a mobile application, identifying an action mapped to the at least one entity, the action representing a deep link into a second mobile application, and providing a control to initiate the action for the entity.

Abstract: Systems and methods prevent or restrict the mining of content on a mobile device. For example, a method may include identifying a mining-restriction mark in low order bits or high order bits in a frame buffer of a mobile device and determining whether the mining-restriction mark prevents mining of content. Mining includes non-transient storage of a copy or derivations of data in the frame buffer. The method may also include preventing the mining of data in the frame buffer when the mining-restriction mark prevents mining.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, to generate a scannable document. In one aspect, a method includes receiving a scan request, wherein the scan request includes a plurality of text images; for each text image of the plurality of text images: rectifying the text image to generate a text image with parallel image lines, generating a plurality of word bounding boxes that enclose one or more connected components in the text image, wherein each word bounding box is associated with a respective word, and generating, for each respective word in the text image, a plurality of points that represent the respective word; combining the plurality of text images to form a single text document; and providing the combined image as a scannable document.

Abstract: A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.

Abstract: Systems and methods are provided for sharing a screen from a mobile device. For example, a method includes receiving an image from a mobile device, performing recognition on the image to identify space-delimited strings, and generating a content graph for the image, the content graph having content nodes that represent at least some of the strings and the content graph having edges that represent a relative position of strings associated with the content nodes connected by the edges. The method may also include repeating the receiving, performing recognition, and generating for a plurality of images, the plurality of images belonging to a session, and generating a combined graph from the plurality of content graphs based on similarity of content nodes between content graphs, the combined graph representing text from the plurality of images in reading order.

Abstract: A method and apparatus for sharing captured media data via a social networking service is described herein. The method includes receiving a list of one or more media data files captured via a mobile (i.e., portable) computing device, the list to include, for each of the media data files, data identifying one or more real-world experiences of a user of the social networking service associated with the respective media data file. The method also includes transmitting information for providing an interface to the mobile computing device to enable the user to share one or more of the media data files in the social network with one or more other users by identifying each media data file with the data identifying a corresponding real-world experience. Furthermore, the method allows for the sharing of data related to the context of each corresponding real-world experience.

Abstract: A server system receives a visual query and information about the current location of the querying device. The server system sends the query and location information to a visual query search system and receives one or more search results in accordance with the visual query and the location information. From the one or more search results, the server system identifies an entity in the visual query. The server system further identifies a client-side action corresponding to the identified entity and creates an actionable search result element configured to launch the client-side action. For example, if the identified entity were a restaurant the actionable search result elements could include buttons to initiate a telephone call, to read reviews, to map the address, or to make a reservation. If the actionable search result is selected, the client system launches the client-side action in an application distinct from the visual query client application.

Abstract: Systems and methods prevent or restrict the mining of content on a mobile device. For example, a method may include determining that content to be displayed on a screen includes content that matches a mining-restriction trigger, inserting a mining-restriction mark in the content that protects at least a portion of the content, and displaying the content with the mining-restriction mark on the screen. As another example, a method may include identifying, by a first application running on a mobile device, a mining-restriction mark in frame buffer data, the mining-restriction mark having been inserted by a second application, and determining whether the mining-restriction mark prevents mining of content. The method may also include preventing mining when the mining-restriction mark prevents mining and, when the mining-restriction mark does not prevent mining, determining a restriction for the data based on the mining-restriction mark and providing the restriction with the data for further processing.

Abstract: A method, system, and computer readable storage medium is provided for identifying textual terms in response to a visual query is provided. A server system receives a visual query from a client system. The visual query is responded to as follows. A set of image feature values for the visual query is generated. The set of image feature values is mapped to a plurality of textual terms, including a weight for each of the textual terms in the plurality of textual terms. The textual terms are ranked in accordance with the weights of the textual terms. Then, in accordance with the ranking the textual terms, one or more of the ranked textual terms are sent to the client system.

Abstract: Implementations provide an improved drag-and-drop operation on a mobile device. For example, a method includes identifying a drag area in a user interface of a first mobile application in response to a drag command, identifying an entity from a data store based on recognition performed on content in the drag area, receiving a drop location associated with a second mobile application, determining an action to perform in the second mobile application based on the drop location, and performing the action in the second mobile action using the entity. Another method may include receiving a selection of a smart copy control for a text input control in a first mobile application, receiving a selected area of a display generated by a second mobile application, identifying an entity in the selected area, automatically navigating back to the text input control, and pasting a description of the entity in the text input control.

Abstract: Systems and methods prevent or restrict the mining of content on a mobile device. For example, a method may include determining that content to be displayed on a screen includes content that matches a mining-restriction trigger, inserting a mining-restriction mark in the content that protects at least a portion of the content, and displaying the content with the mining-restriction mark on the screen. As another example, a method may include identifying, by a first application running on a mobile device, a mining-restriction mark in frame buffer data, the mining-restriction mark having been inserted by a second application, and determining whether the mining-restriction mark prevents mining of content. The method may also include preventing mining when the mining-restriction mark prevents mining and, when the mining-restriction mark does not prevent mining, determining a restriction for the data based on the mining-restriction mark and providing the restriction with the data for further processing.

Abstract: A facial recognition search system identifies one or more likely names (or other personal identifiers) corresponding to the facial image(s) in a query as follows. After receiving the visual query with one or more facial images, the system identifies images that potentially match the respective facial image in accordance with visual similarity criteria. Then one or more persons associated with the potential images are identified. For each identified person, person-specific data comprising metrics of social connectivity to the requester are retrieved from a plurality of applications such as communications applications, social networking applications, calendar applications, and collaborative applications. An ordered list of persons is then generated by ranking the identified persons in accordance with at least metrics of visual similarity between the respective facial image and the potential image matches and with the social connection metrics.

Abstract: A method and apparatus for enabling dynamic product and vendor identification and the display of relevant purchase information are described herein. According to embodiments of the invention, a recognition process is executed on sensor data captured via a mobile computing device to identify one or more items, and to identify at least one product associated with the one or more items. Product and vendor information for the at least one product is retrieved and displayed via the mobile computing device. In the event a user gesture is detected in response to displaying the product and vendor information data, processing logic may submit a purchase order for the product (e.g., for an online vendor) or contact the vendor (e.g., for an in-store vendor).

Abstract: Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. Snapshots associated with use of a computing device by a user are received. Each snapshot is based on content presented to the user. The snapshots are evaluated. For each respective snapshot, a respective set of entities indicated by the respective snapshot is identified. Indications of the respective set of entities and a respective timestamp indicating a respective time that the respective snapshot was captured are associated and stored. Based on a first snapshot of the snapshots, a first time to present one or more information cards to the user is determined. At the first time, entities having a time stamp that corresponds to the first time are located. An information card is generated based on the located entities. The generated information card is provided for presentation to the user.