A High-Realistic Texture Mapping Algorithm Based on Image Sequences

Abstract

3D reconstruction using multiple views allows for the restoration of a complete geometric model, but does not produce textural effects. Most of the existing texture mapping methods are aimed at the scanning reconstruction models, and few of them can be used to deal with the models with large amount of data and complex structure. We propose a high-realistic texture mapping algorithm based on image sequences. Firstly, the image sequence is sampled by using the spatio-temporal adaptive method. Then, the parameters of the camera and the size of each image are extracted by means of the Bundler, and the optimal texture image is selected for each triangular patch through the Markov random field. Finally, due to excessive loading of image data, it is necessary to reduce the texture data and only retain the effective parts mapped onto each triangular patch. Our method ensures that the resolution of the model after texture mapping is higher, and there is no obvious texture seam.