This paper describes an automatic dense correspondence approach to match two given isometric or nearly isometric 3D shapes which have non-rigid deformations. Our method is to improve the described ability of the assignment matrix as much as possible and solve the resolution composed of assignment matrices by using a combinatorial optimization algorithm. First, we construct two linear assignment matrices by using the SHOT and HKS descriptor, which can promote similar points into correspondence. Then, we construct a quadratic assignment matrix by using the heat distribution matrix, which can align a set of pairwise descriptors between a pair of points. In the final, we create a new objective function consisting of three assignment matrices which can adequately describe the matching relationship between points on two non-rigid deformed shapes, and the final optimal solution is obtained by solving the objective function using the projected descent optimization procedure. We show that high-quality dense correspondences can be established for a wide variety of model pairs which may have different poses, surface details. The effectiveness of this method is proven by geodesic error distance statistics from two commonly used datasets with ground truth, and we find that our algorithm is better than other state-of-the-art methods.
Digital watermarking, as an important information security technology, can play a dual role of evidence tracing and encryption in Mobile Police System. In the process of uploading photographic pictures, the poor connectivity and stability of wireless network will greatly affect the robustness of watermarking algorithm. In this study, we proposed a blind watermarking algorithm based on SIFT feature points meanwhile with the idea of spread spectrum.The algorithm extracts sufficient sub-blocks of the host image using feature points to achieve high invisibility and extends multiple times of the original watermark to achieves high robustness and security. Experiment results show that the invisibility and robustness of watermark by using SIFT feature points are better than several other feature extractors and the algorithm meets the application requirements of Mobile Police System.