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Automated photo-consistency test for voxel colouring based on fuzzy adaptive hysteresis thresholding

机译：基于模糊自适应滞后阈值的体素着色自动光一致性测试

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摘要

Voxel colouring is a popular method for reconstructing a three-dimensional surface model from a set of a few calibrated images. However, the reconstruction quality is largely dependent on a thresholding procedure allowing the authors to decide, for each voxel, whether it is photo-consistent or not. Nevertheless, in addition to the absence of any information on the neighbouring voxels during the photo-consistency test, it is extremely difficult to define the appropriate thresholds, which should be precise and stable on all surface voxels. In this study, the authors propose an automated photo-consistency test based on fuzzy hysteresis thresholding. The proposed method allows the incorporation of the spatial coherence during volume reconstruction, while avoiding `floating voxels' and holes. Moreover, the ambiguity of choosing the thresholds is extremely minimised by defining a fuzzy degree of membership of each voxel into the class of consistent voxels. Also, there is no need for preset thresholds since the hysteresis ones are defined automatically and adaptively depending on the number of images that the voxel is projected onto. Preliminary results are very promising and demonstrate that the proposed method performs automatically precise and smooth volumetric scene reconstruction.
机译：体素着色是一种从一组几个校准图像中重建三维表面模型的流行方法。但是，重建质量在很大程度上取决于阈值处理程序，允许作者为每个体素确定其是否具有光一致性。但是，除了在光一致性测试过程中在相邻体素上没有任何信息之外，定义合适的阈值极其困难，该阈值在所有表面体素上都应该是精确且稳定的。在这项研究中，作者提出了一种基于模糊滞后阈值的自动光一致性测试。所提出的方法允许在体积重建期间合并空间相干性，同时避免“浮动体素”和孔洞。此外，通过将每个体素的模糊隶属度定义为一致体素的类别，极大地减小了选择阈值的不确定性。同样，由于磁滞阈值是根据体素投影到的图像数量自动且自适应地定义的，因此不需要预设阈值。初步结果是非常有希望的，并证明了所提出的方法可以自动执行精确，平滑的体积场景重建。

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