Hierarchical Voxel Block Hashing for Efficient Integration of Depth Images
Hierarchical Voxel Block Hashing for Efficient Integration of Depth Images
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DOI：
10.1109/lra.2015.2512958
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发表时间：
2016
影响因子：
5.2
通讯作者：
O. Kähler;V. Prisacariu;Julien P. C. Valentin;D. W. Murray
中科院分区：
文献类型：
--
作者：
O. Kähler;V. Prisacariu;Julien P. C. Valentin;D. W. Murray
许多现代3D重建方法使用截断符号距离函数来体积地积累信息。虽然这通常会使用具有固定体素大小的规则网格，但并不是场景的所有部分都需要以相同的细节级别表示。例如，一个平面表需要较少的细节比一个高度结构化的键盘上it. We介绍了一种新的表示体积的3D数据，使用哈希函数，而不是树访问场景的各个块，但它仍然提供不同的分辨率水平。我们表明，我们的数据结构提供了有效的访问和操作功能，可以很好地并行化，并描述了一种自动的方式选择适当的分辨率为场景的不同部分。我们嵌入新的表示在系统中的同时定位和映射RGB-D图像，也调查插值例程的不规则网格的影响。最后，我们评估我们的系统在实验中，展示了国家的最先进的表示精度在典型的帧速率约100 Hz，沿着与40%的内存节省。
Many modern 3D reconstruction methods accumulate information volumetrically using truncated signed distance functions. While this usually imposes a regular grid with fixed voxel size, not all parts of a scene necessarily need to be represented at the same level of detail. For example, a flat table needs less detail than a highly structured keyboard on it. We introduce a novel representation for the volumetric 3D data that uses hash functions rather than trees for accessing individual blocks of the scene, but which still provides different resolution levels. We show that our data structure provides efficient access and manipulation functions that can be very well parallelised, and also describe an automatic way of choosing appropriate resolutions for different parts of the scene. We embed the novel representation in a system for simultaneous localization and mapping from RGB-D imagery and also investigate the implications of the irregular grid on interpolation routines. Finally, we evaluate our system in experiments, demonstrating state-of-the-art representation accuracy at typical frame-rates around 100 Hz, along with 40% memory savings.