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:
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. Finally, at least one person identifier from the list is sent to the requester.
Abstract:
In one embodiment the present invention is a method for populating and updating a database of images of landmarks including geo-clustering geo-tagged images according to geographic proximity to generate one or more geo-clusters, and visual-clustering the one or more geo-clusters according to image similarity to generate one or more visual clusters. In another embodiment, the present invention is a system for identifying landmarks from digital images, including the following components: a database of geo-tagged images; a landmark database; a geo-clustering module; and a visual clustering module. In other embodiments the present invention may be a method of enhancing user queries to retrieve images of landmarks, or a method of automatically tagging a new digital image with text labels.
Abstract:
A method and apparatus for enabling a searchable history of real- world user experiences is described. The method may include capturing media data by a mobile computing device. The method may also include transmitting the captured media data to a server computer system, the server computer system to perform one or more recognition processes on the captured media data and add the captured media data to a history of real- world experiences of a user of the mobile computing device when the one or more recognition processes find a match. The method may also include transmitting a query of the user to the server computer system to initiate a search of the history or real-world experiences, and receiving results relevant to the query that include data indicative of the media data in the history of real- world experiences.
Abstract:
A visual query is received from a client system, along with location information for the client system, and processed by a server system. The server system sends the visual query and the location information to a visual query search system, and receives from the visual query search system enhanced location information based on the visual query and the location information. The server system then sends a search query, including the enhanced location information, to a location-based search system. The search system receives and provides to the client one or more search results to the client system.
Abstract:
Methods and systems for automated identification of celebrity face images are provided that generate a name list of prominent celebrities, obtain a set of images and corresponding feature vectors for each name, detect faces within the set of images, and remove non-face images. An analysis of the images is performed using an intra-model analysis, an inter-model analysis, and a spectral analysis to return highly accurate biometric models for each of the individuals present in the name list. Recognition is then performed based on precision and recall to identify the face images as belonging to a celebrity or indicate that the face is unknown.
Abstract:
Methods and systems for automatic detection of landmarks in digital images and annotation of those images are disclosed. A method for detecting and annotating landmarks in digital images includes the steps of automatically assigning a tag descriptive of a landmark to one or more images in a plurality of text-associated digital images to generate a set of landmark- tagged images,learning an appearance model for the landmark from the set of landmark-tagged images, and detecting the landmark in a new digital image using the appearance model. The method can also include a step of annotating the new image with the tag descriptive of the landmark.
Abstract:
An image input is obtained from a computing device when an image sensor of the computing device is directed to a scene. At least an object of interest in the scene is determined, and a label is determined for the object of interest. A search input is received from the computing device, where the search input is obtained from a mechanism other than the image sensor. An ambiguity is determined from the search input. A search query is determined that augments or replaces the ambiguity based at least in part on the label. A search result is based on the search query.
Abstract:
Implementations generally relate to face template balancing. In some implementations, a method includes generating face templates corresponding to respective images. The method also includes matching the images to a user based on the face templates. The method also includes receiving a determination that one or more matched images are mismatched images. The method also includes flagging one or more face templates corresponding to the one or more mismatched images as negative face templates.
Abstract:
Systems and methods for modeling the occurrence of common image components (e.g., sub-regions) in order to improve visual object recognition are disclosed. In one example, a query image may be matched to a training image of an object. A matched region within the training image to which the query image matches may be determined and a determination may be made whether the matched region is located within an annotated image component of the training image. When the matched region matches only to the image component, an annotation associated with the component may be identified. In another example, sub-regions within a plurality of training image corpora may be annotated as common image components including associated information (e.g., metadata). Matching sub-regions appearing in many training images of objects may be down-weighted in the matching process to reduce possible false matches to query images including common image components.