A9.com, Inc.

VHOEs with expanded acceptance angle ranges are described as well as various systems and methods for fabricating VHOEs with expanded acceptance angle ranges. The VHOE with expanded acceptance angle range may include two or more individual Bragg gratings. The two or more individual Bragg gratings have the same diffraction geometry but with shifted Bragg conditions. Having the same diffraction geometry means when light is incident on the VHOE including two or more individual Bragg gratings, the diffracted light from each of the Bragg gratings is co-linear or overlapping with the diffracted light from the other Bragg gratings. The Bragg condition for each of the Bragg gratings are shifted with respect to each neighboring Bragg grating by an amount up to the acceptance angle range of each individual Bragg grating.

Approaches described and suggested herein relate to generating three-dimensional representations of objects to be used to render virtual reality and augmented reality effects on personal devices such as smartphones and personal computers, for example. An initial surface mesh of an object is obtained. A plurality of silhouette masks of the object taken from a plurality of viewpoints is also obtained. A plurality of depth maps are generated from the initial surface mesh. Specifically, the plurality of depth maps are taken from the same plurality of viewpoints from which the silhouette images are taken. A volume including the object is discretized into a plurality of voxels. Each voxel is then determined to be either inside the object or outside of the object based on the silhouette masks and the depth data. A final mesh is then generated from the voxels that are determined to be inside the object.

A camera is used to capture image data of representations of a physical environment. Planes and surfaces are determined from a representation. The planes and the surfaces are analyzed using relationships there between to obtain shapes and depth information for available spaces within the physical environment. Locations of the camera with respect to the physical environment are determined. The shapes and the depth information are analyzed using a trained neural network to determine items fitting the available spaces. A live camera view is overlaid with a selection from the items to provide an augmented reality (AR) view of the physical environment from an individual location of the locations. The AR view is enabled so that a user can port to a different location than the individual location by an input received to the AR view while the selection from the items remains anchored to the individual location.

Supplemental content can be determined through a server-side process, wherein a primary content provider can obtain the supplemental content from a supplemental content provider before any of the content is sent to the client device initially requesting the primary content. A primary content provider submits a request that can include an authorization token for the primary content provider, a publisher token including a proxy identifier for the user, application, or client device, and other relevant information. The supplemental content provider can verify the information and select targeted content based on the information. The supplemental content can then be provided to the primary content provider for incorporation with the primary content. The primary content provider can adjust the layout or selection before sending to the client device for display.

Systems for testing for a target virus include an analysis device and a sample cartridge. A system for detecting a target virus includes a cartridge and an analysis device. A biological sample is inserted into the cartridge. The cartridge includes reagents and other liquids for processing the biological sample. The cartridge is inserted into the analysis device. The analysis device interacts with the cartridge to complete testing of the biological sample for the presence of the target virus.

Subsets of training data are selected for iterations of a statistical model through a training process. The selection can reduce the amount of data to be processed by selecting the training data that will likely have significant training value for the pass. This can include using a metric such as the loss or certainty to sample the data, such that easy to classify instances are used for training less frequently than harder to classify instances. A cutoff value or threshold can also, or alternatively, be used such that harder to classify instances are not selected for training until later in the process when the model may be more likely to benefit from training on those instances. Sampling can vary between passes for variety, and the cutoff value might also change such that all data instances are eligible for training selection by at least the last iteration.

System and methods are provided that can address cold-start problems in database keyword searches. The search system generates machine-learned values for new item and queries based on historical signals for already existing item and queries. The values are used as input in a ranking model to rank search results for a user query. The initial values for the new item query pairs predict user engagement with the new item query pairs based on historical data for existing item query pairs and increase the visibility of new items to accumulate user interaction data for the new items. After additional user interactions are received, the values are updated using a Bayesian formula.

A waveguide image combiner is used to transmit a monochrome or full-color image in an augmented reality display. The combiner uses multiple stacked waveguides, each having top and bottom substrates. The combiner also uses multiple pairs of incoupling and outcoupling VHOEs, which are sandwiched between the top and bottom substrates, to expand a first FOV and an image expander to expand the second or perpendicular FOV. This suitably provides an expanded FOV that offers a diagonal FOV≥50°, a horizontal FOV≥40 and a vertical FOV≥25°. The combiner also delivers a large horizontal eye box up to 20 mm and a vertical eye box of 10 mm while maintaining high light efficiency of the real scene (e.g. >80%). The system is able to use a light engine based on broadband (10 nm≤Δλ≤40 nm) LEDs and maintain a large horizontal field of view and high transmission of the real imagery.

Images of various views of objects can be captured. An object mesh structure can be created based at least in part on the object images. The object mesh structure represents the three-dimensional shape of the object. Alpha masks indicating which pixels are associated with the object can be used to refine the object mesh structure. A request can be made to view the object from an arbitrary viewpoint which differs from the viewpoints associated with the captured images. A subset of the captured images can be used to create a synthetic image. Different weights can be assigned to the captured image to render a synthetic image that represents the view from the arbitrary viewpoint selected. The input images for the synthetic image can be prefetched, or loaded into memory before the arbitrary view is requested. The images can also be cached for future use or to avoid reloading them for another synthetic image.

A computing device can obtain data describing at least one document, the at least one document referencing at least one media object, wherein a portion of the at least one media object includes one or more characters. The computing device can obtain data describing the one or more characters in the at least one media object in the at least one document. The computing device can generate an updated copy of the at least one document that includes the data describing the one or more characters in the at least one media object. The computing device can present, on a display screen of the computing device and through an interface, the updated copy of the at least one document, wherein the one or more characters in the at least one media object are able to be selected or searched.