Monocular Stereo Vision of Image Feature-aware Interactive Generation

Tong Tian, Genlong Song, Xuan Chen, Yi Li
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Abstract

This paper presents an image feature extraction based monocular stereo vision method. According to the key feature-aware region of the image, the famous interactive segmentation method GrabCut is introduced. Combing with the image correction and affine transformation and stereoscopic generation, the method can get the resemble 3D vision effect include with the shadow generating and object folding from the original cut apart region in 2D space. The algorithm of image feature-aware monocular stereo vision is high effective and efficiency by experiment with several different background complexity samples. It’s readable and interesting in the usage of virtual reality and augment reality. Especially in the field of digital culture publication and naked eye 3D display, has great application value.
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单眼立体视觉图像特征感知交互生成
提出了一种基于图像特征提取的单目立体视觉方法。根据图像的关键特征感知区域,引入了著名的交互分割方法GrabCut。该方法结合图像校正、仿射变换和立体生成,可以在二维空间中从原始切割区域生成阴影和物体折叠,从而获得类似三维的视觉效果。通过对不同背景复杂度样本的实验,证明了图像特征感知单眼立体视觉算法的有效性和高效性。它在虚拟现实和增强现实的使用方面具有可读性和趣味性。特别是在数字文化出版和裸眼3D显示领域,具有很大的应用价值。
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