Multi-sensor scene brightness analysis to check camera pipeline integrity

1. A computer-implemented method comprising:

receiving, at one or more processing devices at one or more locations, one or more image frames from an imaging device;

receiving, at the one or more processing devices, one or more signals representing outputs of one or more light sensors of a device, wherein the one or more light sensors are different from the imaging device, and the one or more light sensors and the imaging device are located in a same environment;

estimating, by the one or more processing devices based on the one or more image frames, one or more illuminance values;

determining, by the one or more processing devices, a degree of correlation between (i) a first illuminance, represented by the one or more illuminance values, that indicates an illuminance of a scenery captured in the one or more image frames, and (ii) a second illuminance, represented by the one or more signals, that indicates an illuminance of the same environment in which the one or more light sensors and the imaging device are located;

determining, by the one or more processing device, that the degree of correlation fails to satisfy a threshold condition; and

in response to determining that the degree of correlation fails to satisfy the threshold condition, determining, by the one or more processing devices, presence of an adverse condition associated with the device.

2. The computer-implemented method of claim 1 , wherein the adverse condition comprises one of hardware hijack or hardware malfunction.

3. The computer-implemented method of claim 2 , wherein the hardware comprises at least one of a camera and the one or more light sensors of the device.

4. The computer-implemented method of claim 1 , wherein estimating the one or more illuminance values comprises:

estimating an illuminance value corresponding to each image frame based on one or more camera parameters.

5. The computer-implemented method of claim 4 , wherein the one or more camera parameters include at least one of: sensitivity to light (ISO), exposure time, and aperture.

6. The computer-implemented method of claim 1 , wherein determining the degree of correlation between the first illuminance and the second illuminance comprises:

identifying, based on the one or more signals representing outputs of the one or more light sensors of the device, and from a trained model that represents a relationship between illuminance values and corresponding outputs of the one or more light sensors, a predicted illuminance as the second illuminance;

calculating a dissimilarity score between the predicted illuminance and the first illuminance; and

determining the degree of correlation based on the dissimilarity score, wherein a lower dissimilarity score is associated with a higher degree of correlation.

7. The computer-implemented method of claim 1 , wherein determining the degree of correlation between the first illuminance and the second illuminance comprises:

receiving a plurality of image frames;

estimating a first time series of illuminance values corresponding to the plurality of image frames;

estimating a second time series representing the outputs of the one or more light sensors of the device corresponding to the plurality of image frames; and

determining the degree of correlation between the first time series and the second time series.

8. The computer-implemented method of claim 7 , wherein determining the degree of correlation between the first time series and the second time series comprises computing a correlation coefficient.

9. A computer-implemented system, comprising:

one or more processing devices; and

one or more computer memory devices interoperably coupled with the one or more processing devices and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computing devices, perform one or more operations comprising:

receiving, at one or more locations, one or more image frames from an imaging device;

receiving one or more signals representing outputs of one or more light sensors of a device, wherein the one or more light sensors are different from the imaging device, and the one or more light sensors and the imaging device are located in a same environment;

estimating, based on the one or more image frames, one or more illuminance values;

determining a degree of correlation between (i) a first illuminance, represented by the one or more illuminance values, that indicates an illuminance of a scenery captured in the one or more image frames, and (ii) a second illuminance, represented by the one or more signals, that indicates an illuminance of the same environment in which the one or more light sensors and the imaging device are located;

determining that the degree of correlation fails to satisfy a threshold condition; and

in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.

10. The computer-implemented system of claim 9 , wherein the adverse condition comprises one of hardware hijack or hardware malfunction.

11. The computer-implemented system of claim 10 , wherein the hardware comprises at least one of a camera and the one or more light sensors of the device.

12. The computer-implemented system of claim 9 , wherein estimating the one or more illuminance values comprises:

estimating an illuminance value corresponding to each image frame based on one or more camera parameters.

13. The computer-implemented system of claim 12 , wherein the one or more camera parameters include at least one of: sensitivity to light (ISO), exposure time, and aperture.

14. The computer-implemented system of claim 9 , wherein determining the degree of correlation between the first illuminance and the second illuminance comprises:

identifying, based on the one or more signals representing outputs of the one or more light sensors of the device, and from a trained model that represents a relationship between illuminance values and corresponding outputs of the one or more light sensors, a predicted illuminance as the second illuminance;

calculating a dissimilarity score between the predicted illuminance and the first illuminance; and

determining the degree of correlation based on the dissimilarity score, wherein a lower dissimilarity score is associated with a higher degree of correlation.

15. The computer-implemented system of claim 9 , wherein determining the degree of correlation between the first illuminance and the second illuminance comprises:

receiving a plurality of image frames;

estimating a first time series of illuminance values corresponding to the plurality of image frames;

estimating a second time series representing the outputs of the one or more light sensors of the device corresponding to the plurality of image frames; and

determining the degree of correlation between the first time series and the second time series.

16. The computer-implemented system of claim 15 , wherein determining the degree of correlation between the first time series and the second time series comprises computing a correlation coefficient.

17. One or more non-transitory computer-readable storage devices coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving, at one or more locations, one or more image frames from an imaging device;

receiving one or more signals representing outputs of one or more light sensors of a device, wherein the one or more light sensors are different from the imaging device, and the one or more light sensors and the imaging device are located in a same environment;

estimating, based on the one or more image frames, one or more illuminance values;

determining a degree of correlation between (i) a first illuminance, represented by the one or more illuminance values, that indicates an illuminance of a scenery captured in the one or more image frames, and (ii) a second illuminance, represented by the one or more signals, that indicates an illuminance of the same environment in which the one or more light sensors and the imaging device are located;

determining that the degree of correlation fails to satisfy a threshold condition; and

in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.

18. The one or more non-transitory computer-readable storage devices of claim 17 , wherein the adverse condition comprises one of hardware hijack or hardware malfunction.

19. The one or more non-transitory computer-readable storage devices of claim 18 , wherein the hardware comprises at least one of a camera and the one or more light sensors of the device.

20. The one or more non-transitory computer-readable storage devices of claim 17 , wherein estimating the one or more illuminance values comprises:

estimating an illuminance value corresponding to each image frame based on one or more camera parameters.