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US 11,994,405 B2Granted
Methods and systems for determining geographic orientation based on imagery
AssigneeGoogle Inc.
InventorsDaniel Joseph Filip, Zhen Yang
Life of this patent
Estimating the term…
Abstract
The present disclosure is directed to determining geographic orientation based at least in part on imagery. In particular, the methods and systems of the present disclosure can: receive data generated by a camera (118) and representing imagery that includes at least a portion of a physical real-world environment comprising the camera (118) and a travelway (312); and determine, based at least in part on the data and a machine-learning model, a geographic orientation of the camera (118) with respect to the travelway (312).
Claims15
A computer-implemented method comprising:
- receiving, by a computing system, data generated by a camera and representing imagery that includes at least a portion of a physical real-world environment comprising the camera and a travelway;
- estimating a position of a light source based on a time of day associated with the imagery;
- and
- determining, by the computing system, a geographic orientation of the camera with respect to the travelway, wherein the geographic orientation of the camera with respect to the travelway further comprises:
- determining a geographic location of the camera;
- and
- selecting, based at least in part on the geographic location of the camera, a machine-learning model from amongst a plurality of different machine-learning models for determining geographic orientations of cameras with respect to travelways, the plurality of different machine-learning models being based at least in part on training data comprising imagery from different corresponding geographic regions, the machine-learning model being based at least in part on training data comprising imagery from a geographic region comprising the geographic location of the camera, the imagery from the geographic region not including imagery that comprises the travelway.
4 more elements
A system comprising:
- one or more processors;
- and
- a memory storing instructions that when executed by the one or more processors cause the system to perform operations comprising:
- receiving data generated by a camera and representing imagery that includes at least a portion of a physical real-world environment comprising the camera and a travelway;
- estimating a position of a light source based on a time of day associated with the imagery;
- determining a geographic orientation of the camera with respect to the travelway, wherein the geographic orientation of the camera with respect to the travelway further comprises:
- determining a geographic location of the camera;
- and
- selecting, based at least in part on the geographic location of the camera, a machine-learning model from amongst a plurality of different machine-learning models for determining geographic orientations of cameras with respect to travelways, the plurality of different machine-learning models being based at least in part on training data comprising imagery from different corresponding geographic regions, the machine-learning model being based at least in part on training data comprising imagery from a geographic region comprising the geographic location of the camera, the imagery from the geographic region not including imagery that comprises the travelway.
6 more elements
One or more non-transitory computer-readable media comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
- receiving data generated by a camera and representing imagery that includes at least a portion of a physical real-world environment comprising the camera and a travelway having a known orientation with respect to the physical real-world environment;
- estimating a position of a light source based on a time of day associated with the imagery;
- determining a geographic orientation of the camera with respect to the travelway, wherein the geographic orientation of the camera with respect to the travelway further comprises:
- determining a geographic location of the camera;
- and
- selecting, based at least in part on the geographic location of the camera, a machine-learning model from amongst a plurality of different machine-learning models for determining geographic orientations of cameras with respect to travelways, the plurality of different machine-learning models being based at least in part on training data comprising imagery from different corresponding geographic regions, the machine-learning model being based at least in part on training data comprising imagery from a geographic region comprising the geographic location of the camera, the imagery from the geographic region not including imagery that comprises the travelway.
3 more elements
Dependencies are inferred from the claim text.