Abstract: A computer device includes a processor configured to simulate a virtual environment based on a set of virtual environment parameters, and perform ray tracing to render a view of the simulated virtual environment. The ray tracing includes generating a plurality of rays for one or more pixels of the rendered view of the simulated virtual environment. The processor is further configured to determine sub-pixel data for each of the plurality of rays based on intersections between the plurality of rays and the simulated virtual environment, and store the determined sub-pixel data for each of the plurality of rays in an image file.

Abstract: A computer device includes a processor configured to simulate a virtual environment based on a set of virtual environment parameters, and perform ray tracing to render a view of the simulated virtual environment. The ray tracing includes generating a plurality of rays for one or more pixels of the rendered view of the simulated virtual environment. The processor is further configured to determine sub-pixel data for each of the plurality of rays based on intersections between the plurality of rays and the simulated virtual environment, and store the determined sub-pixel data for each of the plurality of rays in an image file.

Abstract: A computer device includes a processor configured to simulate a virtual environment based on a set of virtual environment parameters, and perform ray tracing to render a view of the simulated virtual environment. The ray tracing includes generating a plurality of rays for one or more pixels of the rendered view of the simulated virtual environment. The processor is further configured to determine sub-pixel data for each of the plurality of rays based on intersections between the plurality of rays and the simulated virtual environment, and store the determined sub-pixel data for each of the plurality of rays in an image file.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: A computer device includes a processor configured to simulate a virtual environment based on a set of virtual environment parameters, and perform ray tracing to render a view of the simulated virtual environment. The ray tracing includes generating a plurality of rays for one or more pixels of the rendered view of the simulated virtual environment. The processor is further configured to determine sub-pixel data for each of the plurality of rays based on intersections between the plurality of rays and the simulated virtual environment, and store the determined sub-pixel data for each of the plurality of rays in an image file.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: A computer device is provided that includes a processor configured to simulate a virtual environment based on a set of virtual environment parameters, and perform ray tracing to render a view of the simulated virtual environment. The ray tracing includes generating a plurality of rays for one or more pixels of the rendered view of the simulated virtual environment. The processor is further configured to determine sub-pixel data for each of the plurality of rays based on intersections between the plurality of rays and the simulated virtual environment, and store the determined sub-pixel data for each of the plurality of rays in an image file.

Abstract: Various technologies pertaining to crowd sourcing data about an entity, such as a business, are described. Additionally, technologies pertaining to inferring metadata about the entity based upon crowd sourced data are described. A sensor in a mobile computing device is activated responsive to a user of the mobile computing device checking in at an entity. Metadata, such as occupancy at the entity, noise at the entity, and the like is inferred using the data captured by the sensor. A search result for the entity includes the metadata.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Abstract: The discussion relates to inventory control. One example can analyze data from sensors to identify items and users in an inventory control environment. The example can detect co-location of an individual user and an individual item at a first location in the inventory control environment at a first time and at a second location in the inventory control environment at a second time.

Abstract: Various technologies pertaining to crowd sourcing data about an entity, such as a business, are described. Additionally, technologies pertaining to inferring metadata about the entity based upon crowd sourced data are described. A sensor in a mobile computing device is activated responsive to a user of the mobile computing device checking in at an entity. Metadata, such as occupancy at the entity, noise at the entity, and the like is inferred using the data captured by the sensor. A search result for the entity includes the metadata.

Abstract: The description relates to 3D gesture recognition. One example gesture recognition system can include a gesture detection assembly. The gesture detection assembly can include a sensor cell array and a controller that can send signals at different frequencies to individual sensor cells of the sensor cell array. The example gesture recognition system can also include a gesture recognition component that can determine parameters of an object proximate the sensor cell array from responses of the individual sensor cells to the signals at the different frequencies, and can identify a gesture performed by the object using the parameters.

Abstract: Identifying products in a physical store shopping environment. The method includes, using a first detection method, identifying that a given product likely belongs to a given set of products. The method further includes, using one or more other detection methods, determining that the product is likely a specific product from the given set of products.

Abstract: The discussion relates to visitor-driven, venue-specific media. One implementation can obtain a venue media profile of a venue and obtain visitor profiles of visitors at the venue. This implementation can generate a playlist of visitor-driven, venue specific media based on both the venue media profile and the visitor profiles.

Abstract: Identifying products in a physical store shopping environment. The method includes, using a first detection method, identifying that a given product likely belongs to a given set of products. The method further includes, using one or more other detection methods, determining that the product is likely a specific product from the given set of products.