Adaptive content-aware correction for wide-angle portrait photos

Portraits near the periphery of wide-angle photos often suffer conspicuous distortions. With the popularity of wide-angle lenses on mobile phones, portrait correction, which removes portrait distortion in wide-angle photos, has attracted widespread attention as a form of content-aware warping. Existing portrait correction methods for wide-angle photos using uniform quad meshes take a long time to optimize the correction. Most of them focus only on correcting facial distortions, leading to inconsistency between people's heads and bodies after correction. This study proposes an efficient method to remove portrait distortions in wide-angle perspective photos, based on a triangle mesh. We generate an adaptive mesh tailored to the image content with relatively few vertices. According to the characteristics of the triangle mesh, we tailor three smooth and intuitive energy terms for the human area, background area, and boundary to minimize portrait distortions. Our algorithm can easily be extended to allow further geometric constraints, such as line constraints. Experimental results show that our method is robust for photos with various fields of view. Comparisons to the state-of-the-art demonstrate that our method achieves significant improvements in optimization efficiency and consistency of heads and bodies.