Matthew Bailey, Jean-Yves Guillemaut (2020)A Novel Depth from Defocus Framework Based on a Thick Lens Camera Model, In: 2020 International Conference on 3D Vision (3DV)pp. 1206-1215 IEEE

Reconstruction approaches based on monocular defocus analysis such as Depth from Defocus (DFD) often utilise the thin lens camera model. Despite this widespread adoption, there are inherent limitations associated with it. Coupled with invalid parameterisation commonplace in literature, the overly-simplified image formation it describes leads to inaccurate defocus modelling; especially in macro-scale scenes. As a result, DFD reconstructions based around this model are not geometrically consistent, and are typically restricted to single-view applications. Subsequently, the handful of existing approaches which attempt to include additional viewpoints have had only limited success.In this work, we address these issues by instead utilising a thick lens camera model, and propose a novel calibration procedure to accurately parameterise it. The effectiveness of our model and calibration is demonstrated with a novel DFD reconstruction framework. We achieve highly detailed, geometrically accurate and complete 3D models of real-world scenes from multi-view focal stacks. To our knowledge, this is the first time DFD has been successfully applied to complete scene modelling in this way.