Assuming I have two camera or other sensor feeds, is there an algorithm that gives an estimate of how likely it is that they point at/derive data from the same scene (possibly from different angles, with different modalities, filters and perspectives)?

Perhaps a measure of how easily the data streams could be related/reduced to a common cause?

Simple correlation does not seem to suffice here, since the signals may only be indirectly (and nonlinearly) related and do not necessarily have the same "shape".

This seems to be related, but not the same as the image registration problem.

Assuming I have two sensor feeds, is there an algorithm that gives an estimate of how likely it is that they point at/derive data from the same scene (possibly from different angles, with different modalities, filters and perspectives)?

Perhaps a measure of how easily the data streams could be related/reduced to a common cause?

Simple correlation does not seem to suffice here, since the signals may only be indirectly (and nonlinearly) related and do not necessarily have the same "shape".

This seems to be related, but not the same as the image registration problem.

Assuming I have two camera or other sensor feeds, is there an algorithm that gives an estimate on how likely it is that these cameras point at the same scene (possibly from different angles, with different sensors, filters and lighting conditions)?

Simple correlation does not seem to be sufficient here, since the signals may only be indirectly (and nonlinearly) related and do not necessarily have the same "shape".

This seems to be related, but not the same as the image registration problem.

Assuming I have two camera or other sensor feeds, is there an algorithm that gives an estimate of how likely it is that they point at/derive data from the same scene (possibly from different angles, with different modalities, filters and perspectives)?

Perhaps a measure of how easily the data streams could be related/reduced to a common cause?

Simple correlation does not seem to suffice here, since the signals may only be indirectly (and nonlinearly) related and do not necessarily have the same "shape".

This seems to be related, but not the same as the image registration problem.