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Stochastic refinement of the visual hull to satisfy photometric and silhouette consistency constraints

机译:视觉船体的随机细化,以满足光度法和剪影一致性约束

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An iterative method for reconstructing a 3D polygonal mesh and color texture map from multiple views of an object is presented. In each iteration, the method first estimates a texture map given the current shape estimate. The texture map and its associated residual error image are obtained via maximum a posteriori estimation and reprojection of the multiple views into texture space. Next, the surface shape is adjusted to minimize residual error in texture space. The surface is deformed towards a photometrically-consistent solution via a series of 1D epipolar searches at randomly selected surface points. The texture space formulation has improved computational complexity over standard image-based error approaches, and allows computation of the reprojection error and uncertainty for any point on the surface. Moreover, shape adjustments can be constrained such that the recovered model's silhouette matches those of the input images. Experiments with real world imagery demonstrate the validity of the approach.
机译:呈现了从对象的多个视图重建3D多边形网格和颜色纹理映射的迭代方法。在每次迭代中,该方法首先估计给定当前形状估计的纹理图。通过最大的后验估计和将多个视图的重分重新注入到纹理空间中获得纹理图及其相关的残差图像。接下来,调整表面形状以最小化纹理空间中的残余误差。通过随机选择的表面点,通过一系列1D末面搜索朝向光学算法溶液变形。纹理空间配方在标准的基于图像的误差方法上提高了计算复杂性,并允许计算表面上任何点的重注误差和不确定性。此外,可以约束形状调整,使得恢复的模型的轮廓与输入图像的轮廓匹配。现实世界图像的实验表明了这种方法的有效性。

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