A distributed system for real-time volume reconstruction

Borovikov, Eugene; Davis, Larry S.

doi:10.1109/camp.2000.875976

Cited by 43 publications

(31 citation statements)

References 6 publications

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“…V, this approach exploits the spatial clustering of typical real data [32], [1], [14], allowing a significant reduction of the reconstruction computational time. Different strategies to distribute the computation burden over a camera network have been considered in [3], [5], [6], [15].…”

Section: Introductionmentioning

confidence: 99%

Affinity-based distributed algorithm for 3D reconstruction in large scale Visual Sensor Networks

Masiero¹,

Cenedese

2014

2014 American Control Conference

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In recent years, Visual Sensor Networks have emerged as an interesting category of distributed sensor-actor systems to retrieve data from the observed scene and produce information. Indeed, the request for accurate 3D scene reconstruction in several applications is leading to the development of very large systems and more specifically to large scale motion capture systems. When dealing with such huge amount of data from a large number of cameras it becomes very hard to make real time reconstruction on a single machine.Within this context, a distributed approach for reconstruction on large scale camera networks is proposed. The approach is based on geometric triangulation performed in a distributed fashion on the computational grid formed by the camera network organized into a tree structure. Since the computational performance of the algorithm strongly depends on the order in which cameras are paired, to optimize the reconstruction a pairing strategy is designed that relies on an affinity score among cameras. This score is computed from a probabilistic perspective by studying the variance of the 3D target reconstruction error and resorting to a normalized cut graph partitioning.The scaling laws and the results obtained in simulation suggest that the proposed strategy allows to obtain a significant reduction of the computational time.

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Section: Introductionmentioning

confidence: 99%

Affinity-based distributed algorithm for 3D reconstruction in large scale Visual Sensor Networks

Masiero¹,

Cenedese

2014

2014 American Control Conference

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“…Cheung et al [7] present a voxel-based system which achieves a frame rate of 16 fps using 5 cameras at a voxel resolution of 64 3 . Borovikov et al [4,5] propose a system using a voxel-based reconstruction method. They report frame rates of about 10 fps using 14 cameras at a volume resolution of 64 3 .…”

Section: Introductionmentioning

confidence: 99%

Efficient visual hull computation for real-time 3D reconstruction using CUDA

Ladikos

Benhimane

Navab

2008

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

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“…discrete 3D models made of elementary parallelepipedic cells. Interestingly, several systems in this category [4,12,3,18] use a distribution scheme over a PC cluster to speed up computations and hence, provide some kind of control over the model precision and the process speed. However, voxel based methods are still imprecise unless a huge number of voxels is used.…”

Section: Introductionmentioning

confidence: 99%

The GrImage Platform: A Mixed Reality Environment for Interactions

Allard

Franco

Ménier

et al. 2006

Fourth IEEE International Conference on Computer Vision Systems (ICVS'06)

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In this paper, we present a scalable architecture to compute, visualize and interact with 3D dynamic models of real scenes. This architecture is designed for mixed reality applications requiring such dynamic models, tele-immersion for instance. Our system consists in 3 main parts: the acquisition, based on standard firewire cameras; the computation, based on a distribution scheme over a cluster of PC and using a recent shape-from-silhouette algorithm which leads to optimally precise 3D models; the visualization, which is achieved on a multiple display wall. The proposed distribution scheme ensures scalability of the system and hereby allows control over the number of cameras used for acquisition, the frame-rate, or the number of projectors used for high resolution visualization. To our knowledge this is the first completely scalable vision architecture for real time 3D modeling, from acquisition to visualization through computation. Experimental results show that this framework is very promising for real time 3D interactions.

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A distributed system for real-time volume reconstruction

Cited by 43 publications

References 6 publications

Affinity-based distributed algorithm for 3D reconstruction in large scale Visual Sensor Networks

Affinity-based distributed algorithm for 3D reconstruction in large scale Visual Sensor Networks

Efficient visual hull computation for real-time 3D reconstruction using CUDA

The GrImage Platform: A Mixed Reality Environment for Interactions

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