Abstract: A method comprising: receiving, from a user device at a first location, first image information of a surrounding environment of the user device; determining further image information of the surrounding environment of the user device at the first location, wherein the further image information is required for generating a spatial anchor in the model, wherein the spatial anchor point links the first real-world location of the user device to a corresponding location in the model; providing guidance information to the user device for capturing the further image information; receiving the further image information from the user device; and generating a spatial anchor point in the model based on the first image information and the further image information; wherein following generation of the spatial anchor point, the spatial anchor point is discoverable to one or more users of the model to provide information of the first location.

Abstract: A system for contextual interpretation of a three-dimensional scene includes an object recognition engine that analyzes scene data collected from the three-dimensional scene to identify at least one object present in the three-dimensional scene. The system further includes a contextual inference engine trained on a context data training set to analyze context of the scene by identifying a potential contextual inference associated in memory with the at least one object identified by the object recognition engine; comparing the scene data to a subset of the context data training set identified as satisfying the potential contextual inference; and outputting scene context information conveying the potential contextual inference responsive to a determination that the scene data and the subset of the context data train set satisfy a predetermined correlation.

Abstract: A location system includes two entities that are attempting to co-locate one another. The entities detect and transmit locating information, such as image/video data identifying information, image/video data of the environment, audio data of the environment, or detected signals, to either the other entity or a micro-location server. Analysis is performed on the signals to determine whether the entities are in the same or a similar proximity. Example analysis includes facial recognition of a user (a first entity) in video data captured by a vehicle (a second entity). If the data satisfies a location matching condition (the entities are in a close proximity), then a location refining signal is generated and transmitted to one or both of the entities.

Abstract: A system for contextual interpretation of a three-dimensional scene includes an object recognition engine that analyzes scene data collected from the three-dimensional scene to identify at least one object present in the three-dimensional scene. The system further includes a contextual inference engine trained on a context data training set to analyze context of the scene by identifying a potential contextual inference associated in memory with the at least one object identified by the object recognition engine; comparing the scene data to a subset of the context data training set identified as satisfying the potential contextual inference; and outputting scene context information conveying the potential contextual inference responsive to a determination that the scene data and the subset of the context data train set satisfy a predetermined correlation.

Abstract: Systems, apparatuses, services, platforms, and methods are discussed herein that provide assistance for user interface devices. In one example, an assistance application is provided comprising an imaging system configured to capture an image of a scene, an interface system configured to provide data associated with the image to a distributed assistance service that responsively processes the data to recognize properties of the scene and establish feedback for a user based at least on the properties of the scene, and a user interface configured to provide the feedback to the user.