Sculpture 3D Modeling Method Based on Image Sequence
Author(s) -
Xiaofei Liu
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/9916725
Subject(s) - computer vision , computer science , robustness (evolution) , artificial intelligence , coding (social sciences) , sequence (biology) , feature (linguistics) , computer graphics (images) , mathematics , biochemistry , chemistry , statistics , genetics , linguistics , philosophy , biology , gene
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.
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