Abstract
This thesis first introduces the basic principles of model-based image sequence coding technology, then discusses in detail the specific steps in various implementation algorithms, and proposes a basic feature point calibration required in three-dimensional motion and structure estimation. This is a simple and effective solution. Aiming at the monocular video image sequence obtained by only one camera, this paper introduces the 3D model of the sculpture building into the pose tracking framework to provide initial depth information. The whole posture tracking framework can be divided into three parts, namely, the construction of the initial sculpture model, the posture tracking between frames, and the robustness processing during continuous tracking. In order to reduce the complexity of calculation, this paper proposes a new three-dimensional mesh model and a moving image restoration algorithm based on this model. At the same time, the influence of the intensity and direction factors in the scene is added, the simulation results are given, and the next step is discussed. The optimization work that needs to be done.
Highlights
Introduction e data acquisition and3D modeling of sculpture buildings are important contents of the construction of digital cities and smart cities. e 3D modeling method based on closerange image sequences uses ordinary digital cameras as image acquisition equipment, which has low cost, high efficiency, and low labor intensity
The sparse image contour reconstruction techniques of sculpture points mainly include the following, which are based on RGB image reconstruction method, block size reconstruction method, point distribution model method, etc. [4]. e traditional three-dimensional 3D model theory can accurately restore the 3D model of the object and can adjust the light intensity and the selection of texture features artificially, so it has been widely used in mechanical manufacturing, construction engineering, game animation, etc
Control points and check points can be divided into two groups. e first group is distributed on the ground in the 300 m × 300 m experimental sculpture area, with a total of 25 measuring points used for the construction of the 3D model in the area and its accuracy evaluation; the second group is distributed in the area. ere are 98 measuring points on the exterior surface of the sculpture building, which are used for the construction of the refined model of the single building and its accuracy evaluation. e first group of 25 measuring points are evenly distributed in the test area of 300 m × 300 m, with a diameter of 1 cm and a length of 1 cm
Summary
Received 10 March 2021; Revised 8 April 2021; Accepted 15 April 2021; Published 22 April 2021. Some scanning devices can even obtain the internal structure data of the object It does not output two-dimensional images but contains a digital model file of the threedimensional space coordinates and the color of each sampling point on the surface. Is method uses numerical methods to detect and match feature point sets in the image, at the same time, recover the camera motion parameters and scene geometry, and obtain the 3D model of the object [18]. E specific 3D model hierarchy process is shown, and after analyzing their advantages and disadvantages, combined with the characteristics of the building ground close-up image, a multifeature complementary local affine invariant feature point detection and matching method is proposed. In the threshold change process, the continuous area composed of the local “black” points (or the “white” points in the reverse process) that have appeared is called the extreme value area. e gray values of the pixels in this area are all less than (or greater than) the gray value of boundary pixels. e detection operator detects homogeneous regions in the image, which depends on the structure of the image itself, so it has the characteristics of covariation with the image affine transformation and linear illumination transformation. e basic principle is to start from the extreme
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