一种基于视觉约束的当前视点画面生成方法

由于视点变化中画面可见性的变化以及在当前视点物体表面的扩张,仅由一幅带深度的源参考图像的三维重投影所得到的目标视点画面存在空洞问题.为此,人们采取多源参考图像的合成方法来解决此问题.如何从具有大量冗余信息的多幅源参考图像中快速提取当前目标视点所需信息，成为基于图像的虚拟环境建模和绘制的关键技术.该文给出一种从多幅源参考图像(目前仅两幅)合成当前视点画面的算法.算法结合正向映射及逆向映射技术完成对当前视点画面的合成，并且利用视觉约束-极线约束这一性质从其他源参考图像中寻找填补空洞的像素,从而避免了整幅参考图像的重投影过程及深度比较.同时,算法利用极线对上像素的排序特性和已有目标图像的信息加速填补空洞像素的搜索.算法在不增加原有图像映射算法复杂度的基础上,大大降低了原有多幅图像合成算法的计算量.

A Method of Image Synthesis for Novel Viewpoints Based on Vision

Due to the visibility change and surface enlargement in the new view as viewpoint moves, 3D reprojection from just one reference image inevitably produces holes in the destination image. In tackling the problem, a common solution is to conduct image synthesis from multiple reference images. However, how to extract the information needed in the novel view from these images with plenty of redundance information becomes one of the key techniques in image-based modeling and rendering. In this paper, a new method of image synthesis from multiple (currently two) reference images is proposed. The method combines forward warping and inverse warping to fulfil the image composition task for a novel viewpoint. In the algorithm, vision constraint-epipolar constraint is employed to search the pixel from other reference images in filling the hole, so as to avoid depth comparison and re-mapping of the whole reference image. Besides, the searching process is accelerated by taking advantage of pixel ordering on pairs of epipolar lines and the information already in the destination image. Without increasing the complexity of previous warping method, this algorithm greatly reduces the computation required in image synthesis from multiple reference images.