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RANSAC / Algebraic graph theory / Singular value decomposition / Graph theory / Graph partition / Spectral clustering / Adjacency matrix / Eigenvalues and eigenvectors / Segmentation / Mathematics / Algebra / Statistics


Single-Cluster Spectral Graph Partitioning for Robotics Applications Edwin Olson, Matthew Walter, Seth Teller, and John Leonard Computer Graphics and Robotics Group Massachusetts Institute of Technology 32 Vassar Street,
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Document Date: 2007-09-17 15:27:28


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File Size: 527,80 KB

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City

Warsaw / /

Company

IBM / Lawrence Berkeley National Laboratory / Robotics Group / Wellesley-Cambridge Press / ACM Press / /

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Facility

Robotics Group Massachusetts Institute of Technology / /

IndustryTerm

k-way algorithms / navigation systems / Particle systems / conventional partitioning algorithms / conventional k-way clustering algorithms / contemporary algorithms / tree search / correct data association solution / possible solution / approximate solution / trivial solution / polynomial time data association algorithm / simultaneous solution / large potential search space / polynomial-time solution / search space / graph partitioning algorithm / k-way partitioning algorithm / /

MarketIndex

set 200 / /

Organization

C. Data Association Data association / Example Data Association / Single-Cluster Spectral Graph Partitioning / US Federal Reserve / RANSAC SCGP / Massachusetts Institute of Technology / Data Association / Pattern Analysis and Machine Intelligence / /

Person

Edwin Olson / Seth Teller / John Leonard / Matthew Walter / /

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Position

teller / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / Lecture Notes in Computer Science / /

Technology

laser / knowledge management / Av / 0.8 Algorithms / polynomial time data association algorithm / SCGP algorithm / conventional partitioning algorithms / GPS / graph partitioning algorithm / Power Method-style algorithms / SCGP-based SLAM algorithm / Hough Transform-style algorithm / /

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