论文标题
从深度图中快速，准确和物体感知的表面正常估计
Fast, Accurate and Object Boundary-Aware Surface Normal Estimation from Depth Maps
论文作者
论文摘要
本文提出了一种快速准确的表面正常估计方法，可以直接在深度图（有组织的点云）上使用。表面正常估计过程被配制为封闭形式的表达。为了减少测量噪声的效果，平均操作以多方向方式使用。多方向正常估计过程将在要有效实施的下一步中进行重新重新制定。最后，提出了一种简单而有效的方法，以消除深度不连续性下错误的正常估计。将所提出的方法与众所周知的表面正常估计算法进行比较。结果表明，所提出的算法不仅在准确性方面优于基线算法，而且还足够快，可以在实时应用中使用。
This paper proposes a fast and accurate surface normal estimation method which can be directly used on depth maps (organized point clouds). The surface normal estimation process is formulated as a closed-form expression. In order to reduce the effect of measurement noise, the averaging operation is utilized in multi-direction manner. The multi-direction normal estimation process is reformulated in the next step to be implemented efficiently. Finally, a simple yet effective method is proposed to remove erroneous normal estimation at depth discontinuities. The proposed method is compared to well-known surface normal estimation algorithms. The results show that the proposed algorithm not only outperforms the baseline algorithms in term of accuracy, but also is fast enough to be used in real-time applications.
