Enhanced depth estimation using deep learning

A method comprising:

• obtaining first gradients of a parameter along a first direction of an image of a three-dimensional object pressed into an elastomeric pad of a retrographic sensor;
• obtaining training data, wherein the training data comprises second gradients of the parameter along a second direction different from the first direction;
• generating a trained statistical model using the first gradients and the training data;
• and
• storing the trained statistical model for subsequent use.

A retrographic sensor comprising:

• a transparent structure;
• a transparent elastomeric pad disposed on a surface of the transparent structure;
• a first light source configured to emit light into the transparent structure along a first direction;
• at least one computer processor;
• and
• at least one non-transitory computer-readable storage medium encoded with a plurality of instructions that, when executed by at least one computer processor, perform a method comprising:
• obtaining first gradients of a parameter along the first direction of an image of a three-dimensional object pressed into the elastomeric pad of the retrographic sensor;
• inputting, to a trained statistical model, the first gradients, wherein the trained statistical model is trained to output second gradients of the parameter along a second direction different from the first direction using the first gradients;
• and
• outputting, from the trained statistical model, the second gradients along the second direction.

A method comprising:

• obtaining first gradients of a parameter along a first direction of an image of a three-dimensional object pressed into an elastomeric pad of a retrographic sensor, wherein the retrographic sensor includes at most two light sources configured to illuminate the elastomeric pad in different directions;
• inputting, to a trained statistical model, the first gradients;
• and
• calculating depth information related to the three-dimensional object based at least in part on an output from the trained statistical model.