论文标题
具有语义先验的多视图立体声
Multi view stereo with semantic priors
论文作者
论文摘要
如今，基于补丁的立体声是一种常用的基于图像的基于图像的技术，用于大规模多视图应用程序中的密集3D重建。这种管道的典型步骤可以总结在立体对选择，深度图计算，深度映射细化以及融合以生成3D中场景的完整而准确的表示。在这项研究中，我们旨在支持通过使用语义先验在开源库OpenMV中实现的标准密集3D重建场景。为此，在深度图融合步骤中，以及在相邻视图的深度图之间的深度一致性检查参考3D场景的同一部分的深度图，我们施加了额外的语义限制，以删除可能的错误并选择性地获得每个标签的分段点云，从而提高自动化此方向。在为了在相邻视图之间保证语义连贯性，可以考虑其他语义标准，以消除属于不同类别中的像素的不匹配。
Patch-based stereo is nowadays a commonly used image-based technique for dense 3D reconstruction in large scale multi-view applications. The typical steps of such a pipeline can be summarized in stereo pair selection, depth map computation, depth map refinement and, finally, fusion in order to generate a complete and accurate representation of the scene in 3D. In this study, we aim to support the standard dense 3D reconstruction of scenes as implemented in the open source library OpenMVS by using semantic priors. To this end, during the depth map fusion step, along with the depth consistency check between depth maps of neighbouring views referring to the same part of the 3D scene, we impose extra semantic constraints in order to remove possible errors and selectively obtain segmented point clouds per label, boosting automation towards this direction. I n order to reassure semantic coherence between neighbouring views, additional semantic criterions can be considered, aiming to elim inate mismatches of pixels belonging in different classes.
