An augmented reality (AR) navigation system: includes an AR display device configured to provide a near-eye display function; and a mobile terminal communicatively connected with the AR display device, where the mobile terminal is configured to send a control instruction to the AR display device, so that the AR display device displays AR content corresponding to the control instruction. Through one or more embodiments disclosed in the present invention, display content of the AR display device may be controlled by the mobile terminal, so that there is no need to identify a target through a complex algorithm such as CV. The technical implementation cost is low and the user experience is high, which can meet the requirements of some specific navigation scenes.

The present disclosure provides a method and apparatus for a route navigation, which relate to the technical fields of computer vision, image processing, augmented reality and the like. An implementation solution is: performing an augmented reality navigation on a current route based on real-time acquired GPS information of a terminal; acquiring SLAM (simultaneous localization and mapping) coordinates of the terminal; converting, in response to determining that the GPS information meets a preset positioning difference condition, the SLAM coordinates into calculated geographic coordinates; and performing an augmented reality navigation on the current route based on the calculated geographic coordinates.

The present disclosure is directed toward systems and methods for an augmented reality transportation system. For example, the systems and methods described herein present an augmented reality environment for a driver or a passenger including augmented reality elements to mark specific locations within a display of real-world surroundings. Additionally, the systems and methods described herein analyze historical information to determine placements for augmented reality elements. The systems and methods also enable a user to share an augmented reality or virtual reality environment with another user.

Information that identifies a location can be received. In response to a receipt of the information that identifies the location, a file can be retrieved. The file can be for the location. The file can include image data and a set of node data. The set of node data can include information that identifies nodes in a neural network, information that identifies inputs of the nodes, and values of weights to be applied to the inputs. In response to a retrieval of the file, the weights can be applied to the inputs of the nodes and the image data can be received for the neural network. In response to an application of the weights and a receipt of the image data, the neural network can be executed to produce a digital map for the location. The digital map for the location can be transmitted to an automotive navigation system.

In some implementations, a computing device can provide a map application providing a representation of a physical structure of venues (e.g., shopping centers, airports) identified by the application. In addition, the application can provide a unique venue directory, providing an easy and visual mechanism to search for categories of points of interest (e.g., clothes, food, restrooms) or specific items within the venue. Search results can be presented on a map of a floor within the venue as well as a listing providing all search results located within the venue.

Aspects of the disclosure relate providing a lane change notification when a vehicle is to perform a lane change. One or more computing devices may generate and display a video, where the video is generated from a perspective of a virtual camera at a default position and default pitch. The one or more computing devices may receive an indication that the vehicle is to perform a lane change from a first lane to a second lane and adjust, after the vehicle receives the indication, the default position and default pitch of the virtual camera to an updated position further above the vehicle relative to ground than the default position and an updated pitch directed more towards the ground than the default pitch. The video may be generated and displayed from the perspective of the virtual camera at the updated position and updated pitch.

Aspects of the disclosure relate to providing an end of trip sequence when a vehicle is nearing its destination. One or more computing devices may generate and display a video indicating a projected trajectory of the vehicle and objects detected by sensors on the vehicle, on a map corresponding to a route the vehicle is currently following, where the video is generated from a perspective of a virtual camera at a default position and default pitch A determination that the vehicle has reached a threshold relative to the route of the vehicle may be made and the position and pitch of the virtual camera may be adjusted to an updated position above the vehicle and a perspective which looks downwards towards a roof of the vehicle. The video may then be generated and displayed from the perspective of the virtual camera at the updated position.

It is possible to display the state of the current route even with a large change in visual field in an easy-to-understand manner. A grouping unit (102) groups a plurality of nodes included in a route on a map into groups having no change in line-of-sight in an order of travel direction on the route. A point generation unit (103) generates, for each of the groups grouped by the route grouping unit, a plurality of points included in a route of the group so that the route is divided into smaller sections by the points from a start point of the group toward an end point of the group. A viewpoint determination unit (104) determines, for each of the plurality of points, a viewpoint in accordance with a condition of the point. A walk-through display unit (105) performs walk-through display for displaying a scenery corresponding to the determined viewpoint.

The present disclosure relates to a method for determining a vehicle pose, predicting a pose (x.sub.k, y.sub.k, θ.sub.k) of vehicle on a map based on sensor data acquired by a vehicle localization system, transforming a set of map road references of a segment of a digital map from a global coordinate system to an image-frame coordinate system of a vehicle-mounted camera based on map data and predicted pose of the vehicle. The transformed set of map road references form a set of polylines in image-frame coordinate system. Identifying a set of corresponding image road reference features in an image acquired by vehicle mounted camera, where each identified road references feature defines a set of measurement coordinates (x.sub.i, y.sub.i) in image-frame. Projecting each of identified set of image road reference features onto formed set of polylines in order to obtain a set of projection points.

Disclosed is a system and method of an advanced intelligent object tracing system utilizing 3D map reconstruction to provide virtual assistance utilizing only camera system and sensors as the main data input. The present disclosure may use a deep learning algorithm and a neural network to perform 3D map generation, distance calculation, object detection and recognition, and utilize augmented reality to display virtual directions.