Variational Perspective Shape from Shading

Many recent methods for perspective shape from shading (SfS) are based on formulations in terms of partial differential equations (PDEs). However, while the quality of such methods steadily improves, their lacking robustness is still an open issue. In this context, variational methods seem to be a promising alternative, since they allow to incorporate smoothness assumptions that have proven to be useful for many other tasks in computer vision. Surprisingly, however, such methods have hardly been considered for perspective SfS so far. In our article we address this problem and develop a novel variational model for this task. By combining building blocks of recent PDE-based methods such as a Lambertian reflectance model and camera-centred illumination with a discontinuitypreserving second-order smoothness term, we obtain a variational method for perspective SfS that offers by construction an improved degree of robustness compared to existing PDE-based approaches. Our experiments confir...

• Type: Journal
• Year: 2015
• Where: SCALESPACE
• Authors: Yong Chul Ju, Andrés Bruhn, Michael Breuß
• Keywords: Computer Vision, SCALESPACE 2015