Camera parameter preconditioning for neural radiance fields

A computing system, comprising:

• a processor;
• and
• a non-transitory, computer-readable medium that, when executed by the processor, causes the processor to perform operations, the operations comprising:
• obtaining a plurality of images, wherein a plurality of sets of parameter values are respectively associated with the plurality of images, each set of parameter values comprising values for a plurality of camera parameters;
• determining a covariance matrix for the plurality of camera parameters with respect to a plurality of projected points generated via evaluation of a projection function at the plurality of sets of parameter values;
• performing a whitening algorithm to identify a preconditioning matrix that, when applied to the plurality of sets of parameter values, results in the covariance matrix being approximately equal to an identity matrix;
• and
• performing an optimization algorithm on the plurality of sets of parameter values, wherein performing the optimization algorithm comprises:
• applying an inverse of the preconditioning matrix to the plurality of sets of parameters in a forward prediction pass;
• and
• applying the preconditioning matrix in a backward gradient pass.

A non-transitory, computer-readable medium that, when executed by a processor, causes the processor to perform operations, the operations comprising:

• obtaining a plurality of images, wherein a plurality of sets of parameter values are respectively associated with the plurality of images, each set of parameter values comprising values for a plurality of camera parameters;
• determining a covariance matrix for the plurality of camera parameters with respect to a plurality of projected points generated via evaluation of a projection function at the plurality of sets of parameter values;
• performing a whitening algorithm to identify a preconditioning matrix that, when applied to the plurality of sets of parameter values, results in the covariance matrix being approximately equal to an identity matrix;
• and
• performing an optimization algorithm on the plurality of sets of parameter values, wherein performing the optimization algorithm comprises:
• applying an inverse of the preconditioning matrix to the plurality of sets of parameters in a forward prediction pass;
• and
• applying the preconditioning matrix in a backward gradient pass.