Fast Preprocessing for Robust Face Sketch Synthesis
This work addresses a domain-specific challenge in computer vision for applications like face recognition, but it is incremental as it builds on existing exemplar-based methods.
The paper tackles the problem of face sketch synthesis under varying lighting conditions by proposing a fast preprocessing method called Bidirectional Luminance Remapping (BLR), which interactively adjusts lighting in training and input photos to improve robustness with minimal computational cost.
Exemplar-based face sketch synthesis methods usually meet the challenging problem that input photos are captured in different lighting conditions from training photos. The critical step causing the failure is the search of similar patch candidates for an input photo patch. Conventional illumination invariant patch distances are adopted rather than directly relying on pixel intensity difference, but they will fail when local contrast within a patch changes. In this paper, we propose a fast preprocessing method named Bidirectional Luminance Remapping (BLR), which interactively adjust the lighting of training and input photos. Our method can be directly integrated into state-of-the-art exemplar-based methods to improve their robustness with ignorable computational cost.