Non-rigid image deformation algorithm based on MRLS-TPS
Huabing Zhou, Yuyu Kuang, Zhenghong Yu, Shiqiang Ren, Anna Dai, Yanduo Zhang, Tao Lü, Jiayi Ma · 2017
In this paper, we propose a novel closed-form transformation estimation method based on moving regularized least squares optimization with thin-plate spline (MRLS-TPS) for non-rigid image deformation. The method takes the user-controlled point-offset-vectors as the input data, and estimates the spatial transformation about the two control point sets for each pixel. To achieve a realistic deformation, we formulates the transformation estimation as a vector-field interpolation problem by a moving regularized least squares method. Unlike MLS, the mapping function is modeled by a non-rigid function thin-plate spline with regularization technique, such that the deformation can satisfy both global linear affine motion and local non-rigid warping. We derive a closed-form solution of the transformation and achieve a fast implementation. In addition, the proposed method can give a wonderful user experience, fast and convenient manipulating. Extensive experiments on real images demonstrated the proposed method outperforms other state-of-the-art methods and the commercial software Adobe PhotoShop CS 6, especially in case of flexible object motion.