Smart depth of field optimization applied to a robotised view camera

TL;DR

This paper introduces a computer-controlled view camera system that uses a mathematical model and optimization algorithms to automatically achieve optimal depth of field, simplifying focus adjustments for high-quality photography.

Contribution

It presents a novel integrated system combining precise hardware, a mathematical model, and optimization algorithms for automated depth of field control in view cameras.

Findings

Validated optimization algorithms on virtual camera models

Successfully implemented on a prototype view camera

Achieved automated focus and depth of field optimization

Abstract

The great flexibility of a view camera allows to take high quality photographs that would not be possible any other way. But making a given object into focus is a long and tedious task, although the underlying laws are well known. This paper presents the result of a project which has lead to the design of a computer controlled view camera and to its companion software. Thanks to the high precision machining of its components, and to the known optical parameters of lenses and sensor, we have been able to consider a reliable mathematical model of the view camera, allowing the acquisition of 3D coordinates to build a geometrical model of the object. Then many problems can be solved, e.g. minimizing the f-number while maintaining the object within the depth of field, which takes the form of a constrained optimization problem. All optimization algorithms have been validated on a virtual view camera before implementation on the prototype