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图像拼接技术在太极拳动画创作中的应用。

Application of Image Mosaic Technology in Tai Chi Animation Creation.

机构信息

College of Physical Education, Luoyang Institute of Science and Technology, Luoyang, Henan 471023, China.

出版信息

Comput Intell Neurosci. 2022 Jan 13;2022:4775189. doi: 10.1155/2022/4775189. eCollection 2022.

Abstract

Panorama can reflect the image seen at any angle of view at a certain point of view. How to improve the quality of panorama stitching and use it as a data foundation in the "smart tourism" system has become a research hotspot in recent years. Image stitching means to use the overlapping area between the images to be stitched for registration and fusion to generate a new image with a wider viewing angle. This article takes the production of "Tai Chi" animation as an example to apply image stitching technology to the production of realistic 3D model textures to simplify the production of animation textures. A handheld camera is used to collect images in a certain overlapping area. After cylindrical projection, the Harris algorithm based on scale space is adopted to detect image feature points, the two-way normalized cross-correlation algorithm matches the feature points, and the algorithm to extract the threshold iteratively removes mismatches. The transformation parameter model is quickly estimated through the improved RANSAC algorithm, and the spliced image is projected and transformed. The Szeliski grayscale fusion method directly calculates the grayscale average of the matching points to fuse the image, and finally, the best stitching method is used to eliminate the ghosting at the image mosaic. Data experiments based on Matlab show that the proposed image splicing technology has the advantages of high efficiency and clear spliced images and a more satisfactory panoramic image visual effect can be achieved.

摘要

全景图可以反映在某一视点的任意视角下的图像。如何提高全景拼接的质量,并将其用作“智能旅游”系统的数据基础,已成为近年来的研究热点。图像拼接是指利用要拼接的图像之间的重叠区域进行注册和融合,以生成具有更宽视角的新图像。本文以“太极拳”动画的制作为例,将图像拼接技术应用于现实 3D 模型纹理的制作中,以简化动画纹理的制作。使用手持相机在一定的重叠区域内采集图像。经过圆柱投影后,采用基于尺度空间的 Harris 算法检测图像特征点,采用双向归一化互相关算法匹配特征点,采用迭代提取阈值的算法去除不匹配点。通过改进的 RANSAC 算法快速估计变换参数模型,并对拼接图像进行投影和变换。Szeliski 灰度融合方法直接计算匹配点的灰度平均值来融合图像,最后,采用最佳拼接方法消除图像拼接处的重影。基于 Matlab 的数据实验表明,所提出的图像拼接技术具有效率高、拼接图像清晰的优点,能够实现更令人满意的全景图像视觉效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5450/8776481/c436bf8941a1/CIN2022-4775189.001.jpg

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