Location mapping for large scale augmented-reality
An Augmented-Reality which performs operations that include: accessing a data object that comprises image data, location data, and orientation data; applying a transformation to the data object to produce a rectified data object; generating a point cloud based on the rectified data object; assigning the point cloud to a location based on at least the location data of the data object; detecting a client device at the location; and loading the point cloud to the client device in response to the detecting the client device at the location.
1. A method comprising:
receiving a request that identifies a location, the request comprising metadata;
accessing a point cloud associated with the location responsive to the request;
determining a contextual condition based on the metadata from the request, the contextual condition including a perspective of the client device and temporal data that indicates a time of day of the request;
identifying a portion of the point cloud based on the contextual condition that includes the perspective and the time of day; and
loading the portion of the point cloud at a client device.
2. The method of claim 1 , wherein the request comprises an image that comprises a set of image features, and the method further comprises:
identifying the location based on the set of image features of the image.
3. The method of claim 1 , wherein the contextual condition includes a connectivity speed of a network associated with the client device.
4. The method of claim 1 , wherein the contextual condition includes user profile data.
5. The method of claim 1 , wherein the request comprises image data, and the method further comprises:
identifying the portion of the point cloud based on the image data.
6. The method of claim 1 , further comprising:
presenting AR content at the client device based on the portion of the point cloud.
7. A system comprising:
a memory; and
at least one hardware processor coupled to the memory and comprising instructions that causes the system to perform operations comprising:
receiving a request that identifies a location, the request comprising metadata;
accessing a point cloud associated with the location responsive to the request;
determining a contextual condition based on the metadata from the request, the contextual condition including a perspective of the client device and temporal data that indicates a time of day of the request;
identifying a portion of the point cloud based on the contextual condition that includes the perspective and the time of day; and
loading the portion of the point cloud at a client device.
8. The system of claim 7 , wherein the request comprises an image that comprises a set of image features, and the operations further comprise:
identifying the location based on the set of image features of the image.
9. The system of claim 7 , wherein the contextual condition includes a connectivity speed of a network associated with the client device.
10. The system of claim 7 , wherein the contextual condition includes user profile data.
11. The system of claim 7 , wherein the request comprises image data, and the method further comprises:
identifying the portion of the point cloud based on the image data.
12. The system of claim 7 , further comprising:
presenting AR content at the client device based on the portion of the point cloud.
13. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
receiving a request that identifies a location, the request comprising metadata;
accessing a point cloud associated with the location responsive to the request;
determining a contextual condition based on the metadata from the request, the contextual condition including a perspective of the client device and temporal data that indicates a time of day of the request;
identifying a portion of the point cloud based on the contextual condition that includes the perspective and the time of day; and
loading the portion of the point cloud at a client device.
14. The non-transitory machine-readable storage medium of claim 13 , wherein the request comprises an image that comprises a set of image features, and the method further comprises:
identifying the location based on the set of image features of the image.
15. The non-transitory machine-readable storage medium of claim 13 , wherein the contextual condition includes a connectivity speed of a network associated with the client device.
16. The non-transitory machine-readable storage medium of claim 13 , wherein the contextual condition includes user profile data.
17. The non-transitory machine-readable storage medium of claim 13 , wherein the request comprises image data, and the method further comprises:
identifying the portion of the point cloud based on the image data.