Abstract

Information acquisition is an important branch of information science. It is the product of the development and cross-integration of traditional sensing technology and other multidisciplines. It is characterized by the high precision, high speed, integration, and intelligence of information acquisition. An important part of information acquisition, it studies how to acquire the geometric structure and scale information of objects in three-dimensional space. With the continuous development of the level, the acquisition of 3D information has become more and more important in scientific research and industrial production. This paper takes 3D information acquisition technology as the main line. From the perspectives of fusion, effectiveness, physical limit, and measurement efficiency, high-resolution 3D information acquisition techniques are studied. In this paper, the upper and lower limb movements of each behavioral segment are segmented according to the difference. An omnidirectional stereo vision sensor composed of a single camera and two secondary conical mirrors is designed, which solves the problems of large size, narrow field of view, and asynchronous image acquisition of traditional binocular vision sensors, effectively ensuring image perspective. The invariance of projection avoids image distortion caused by curved mirror imaging and reduces the difficulty of subsequent work. The three-dimensional Delaunay triangulation algorithm is used to replace the traditional Poisson reconstruction algorithm to generate the triangular mesh model. The triangular mesh model obtained by the multiview stereo reconstruction algorithm is relatively rough. This article uses Zbrush’s ZRemesher and geometric-divide functions to smooth and simplify the model. The results show that the accuracy of the algorithm proposed in this paper is as high as 89.25% in the motion recognition of body elements. The dynamic mapping method is used to map the texture of the triangular mesh model, so that the realism of the model reaches 91.23%.

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