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:
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;
determining a contextual condition associated with the client device;
identifying a portion of the point cloud based on the contextual condition; and
loading the point cloud to the client device based on the identifying the portion of the point cloud based on the contextual condition.
2. The method of claim 1 , wherein the data object includes a video frame, and the accessing the video frame includes:
accessing video data that comprises a set of video frames; and
exporting a portion of the set of video frames, the portion of the set of video frames including the video frame.
3. The method of claim 1 , wherein the applying the transformation includes:
performing linear rectification upon the data object.
4. The method of claim 1 , wherein the data object includes 360 camera data.
5. The method of claim 1 , wherein the detecting the client device at the location includes:
receiving a request that includes an identification of the location from the client device.
6. The method of claim 1 , wherein the method further comprises:
causing display of media content at the client device based on the point cloud.
7. The method of claim 1 , wherein the loading the point cloud to the client device includes:
loading the portion of the point cloud at the client device.
8. The method of claim 1 , wherein the contextual condition includes a connectivity speed of a network associated with the client device.
9. The method of claim 1 , wherein the contextual condition includes a time of day.
10. The method of claim 1 , wherein the contextual condition includes user profile data.
11. The method of claim 1 , wherein the loading the point cloud to the client device includes:
identifying a landmark based on the image data of the data object;
identifying a portion of the point cloud based on the landmark; and
loading the portion of the point cloud at the client device.
12. 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:
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;
determining a contextual condition associated with the client device;
identifying a portion of the point cloud based on the contextual condition; and
loading the point cloud to the client device based on the identifying the portion of the point cloud based on the contextual condition.
13. The system of claim 12 , wherein the data object includes a video frame, and the accessing the video frame includes:
accessing video data that comprises a set of video frames; and
exporting a portion of the set of video frames, the portion of the set of video frames including the video frame.
14. The system of claim 12 , wherein the applying the transformation includes:
performing linear rectification upon the data object.
15. The system of claim 12 , wherein the data object includes 360 camera data.
16. The system of claim 12 , wherein the detecting the client device at the location includes:
receiving a request that includes an identification of the location from the client device.
17. The system of claim 12 , wherein the operations further comprise:
causing display of media content at the client device based on the point cloud.
18. The system of claim 12 , wherein the loading the point cloud to the client device includes:
determining a contextual condition associated with the client device;
loading the portion of the point cloud at the client device.
19. 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:
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;
determining a contextual condition associated with the client device;
identifying a portion of the point cloud based on the contextual condition; and
loading the point cloud to the client device based on the identifying the portion of the point cloud based on the contextual condition.
20. The non-transitory machine-readable storage medium of claim 19 , wherein the data object includes a video frame, and the accessing the video frame includes:
accessing video data that comprises a set of video frames; and
exporting a portion of the set of video frames, the portion of the set of video frames including the video frame.