从多个量化深度图中提高三维表面的精度

Pengfei Wan, Gene Cheung, P. Chou, D. Florêncio, Cha Zhang, O. Au
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引用次数: 3

摘要

从发送方传输压缩的纹理和多视点深度图,可以通过基于深度图像的渲染(DIBR)从任何中间虚拟视点在接收方进行图像合成。研究发现,同一三维场景不同视点的量化深度图构成了对同一信号的多个描述(MD),因此当多个深度图联合考虑时,可以在接收端以更高的精度重建三维场景。本文将多个量化深度图对三维曲面的精度增强作为一个组合优化问题。首先,我们推导出一个引理,它允许我们通过从两个视图中发现量化箱(QB)的特殊交叉点来确定地增加3D点子集的精度。然后,我们使用最短路径公式确定最可能的包含体素的QB相交。实验结果表明,与标准的深度图译码方案相比,该方法可以显著提高深度图译码的精度。
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Precision enhancement of 3D surfaces from multiple quantized depth maps
Transmitting from sender compressed texture and depth maps of multiple viewpoints enables image synthesis at receiver from any intermediate virtual viewpoint via depth-image-based rendering (DIBR). We observe that quantized depth maps from different viewpoints of the same 3D scene constitutes multiple descriptions (MD) of the same signal, thus it is possible to reconstruct the 3D scene in higher precision at receiver when multiple depth maps are considered jointly. In this paper, we cast the precision enhancement of 3D surfaces from multiple quantized depth maps as a combinatorial optimization problem. First, we derive a lemma that allows us to increase the precision of a subset of 3D points with certainty, simply by discovering special intersections of quantization bins (QB) from both views. Then, we identify the most probable voxel-containing QB intersections using a shortest-path formulation. Experimental results show that our method can significantly increase the precision of decoded depth maps compared with standard decoding schemes.
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