Octree-based fusion for realtime 3D reconstruction

Zhang, Ming; Zhao, Fukai; Zheng, Jiyue; Liu, Xinguo

doi:10.1016/j.gmod.2012.09.002

Cited by 124 publications

(87 citation statements)

References 18 publications

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“…As we want to save distance field data so it can be used later for post-processing, motion planning, and Recent works have focused on extending TSDF fusion to larger scenes by compressing the distance field to avoid storing and iterating over empty space. Many have used hierarchal data structures such as octrees or KD-trees to store the TSDF [30,31]. However, these structures suffer from high complexity and complications with parallelism.…”

Section: Related Workmentioning

confidence: 99%

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Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

Klingensmith¹,

Dryanovski²,

Srinivasa³

et al. 2015

Robotics: Science and Systems XI

144

131

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Abstract-We describe CHISEL: a system for real-time housescale (300 square meter or more) dense 3D reconstruction onboard a Google Tango [1] mobile device by using a dynamic spatially-hashed truncated signed distance field [2] for mapping, and visual-inertial odometry for localization. By aggressively culling parts of the scene that do not contain surfaces, we avoid needless computation and wasted memory. Even under very noisy conditions, we produce high-quality reconstructions through the use of space carving. We are able to reconstruct and render very large scenes at a resolution of 2-3 cm in real time on a mobile device without the use of GPU computing. The user is able to view and interact with the reconstruction in real-time through an intuitive interface. We provide both qualitative and quantitative results on publicly available RGB-D datasets [3], and on datasets collected in real-time from two devices.

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Section: Related Workmentioning

confidence: 99%

“…Some works have either used octrees [24,30,31], or use a moving volume [12]. Neither of these approaches is desirable for our application.…”

Section: F the Dynamic Spatially-hashed Tsdfmentioning

confidence: 99%

Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

Klingensmith¹,

Dryanovski²,

Srinivasa³

et al. 2015

Robotics: Science and Systems XI

144

131

View full text Add to dashboard Cite

show abstract

“…Octrees are established in many fields and are often used to alleviate computational burdens. Recent work ( [7,22,27]) uses Octrees for range data integration to map the environment, but employs simple update rules to encompass newly seen data without any optimization whatsoever. For simulation problems these partitioning structures are usually of static auxiliary nature (e.g.…”

Section: Arxiv:160807411v1 [Cscv] 26 Aug 2016mentioning

confidence: 99%

“…In [15,16], the authors deal with spatially adaptive techniques for incompressible flow and state their surprise about the high accuracy of Octree-based mesh refinement even for smallscale structures. The works [7,22,27] use dynamic Octree-based representations to store scene geometry but do no conduct any elaborate schemes for the integration since their main interest is mapping and efficient storage/updates for large-scale problems. [9] introduces a data structure that includes a hierarchical partitioning where each cube uses a runlength encoding.…”

Section: Related Workmentioning

confidence: 99%

An Octree-Based Approach towards Efficient Variational Range Data Fusion

Kehl

Holl²,

Tombari

et al. 2016

Procedings of the British Machine Vision Conference 2016

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Volume-based reconstruction is usually expensive both in terms of memory consumption and runtime. Especially for sparse geometric structures, volumetric representations produce a huge computational overhead. We present an efficient way to fuse range data via a variational Octree-based minimization approach by taking the actual range data geometry into account. We transform the data into Octree-based truncated signed distance fields and show how the optimization can be conducted on the newly created structures. The main challenge is to uphold speed and a low memory footprint without sacrificing the solutions' accuracy during optimization. We explain how to dynamically adjust the optimizer's geometric structure via joining/splitting of Octree nodes and how to define the operators. We evaluate on various datasets and outline the suitability in terms of performance and geometric accuracy.

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“…Researchers have proposed multidimensional data structures such as R-tree [5], Quadtree [6,7], and Octree [8], all of which enable efficient performance in data storage and searching systems. Quadtree is commonly used in the two-dimensional space, whereas Octree is more popular in the three-dimensional space common in many application systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic multidimensional index for large-scale cloud data

Dong

et al. 2016

J Cloud Comp

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Although several cloud storage systems have been proposed, most of them can provide highly efficient point queries only because of the key-value pairs storing mechanism. For these systems, satisfying complex multi-dimensional queries means scanning the whole dataset, which is inefficient. In this paper, we propose a multidimensional index framework, based on the Skip-list and Octree, which we refer to as Skip-Octree. Using a randomized skip list makes the hierarchical Octree structure easier to implement in a cloud storage system. To support the Skip-Octree, we also propose a series of index operation algorithms including range query algorithm, index maintenance algorithms, and dynamic index scaling algorithms. Through experimental evaluation, we show that the Skip-Octree index is feasible and efficient.

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Octree-based fusion for realtime 3D reconstruction

Cited by 124 publications

References 18 publications

Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

Chisel: Real Time Large Scale 3D Reconstruction Onboard a Mobile Device using Spatially Hashed Signed Distance Fields

An Octree-Based Approach towards Efficient Variational Range Data Fusion

Dynamic multidimensional index for large-scale cloud data

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