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Spectral Curvature Clustering

Technology #z07139

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Affine SubspacesSpectral Curvature ClusteringVideo Analysis Using Linear Modeling
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Researchers
Gilad Lerman, PhD
Professor, School of Mathematics, College of Science and Engineering
External Link (www2.math.umn.edu)
Managed By
Andrew Morrow
Technology Licensing Officer

Video Analysis Using Linear Modeling

The system for Spectral Curvature Clustering (SCC) is software that analyzes photo and video to estimate affine subspaces. The SCC consists of relatively basic software, which allows it to run at great speed. The SCC uses linear modeling to estimate the affine subspaces. The SCC is designed to be used with other computer video analytic systems to provide greater depth to the analysis and results that are produced. The SCC is especially advanced in the area of background noise tolerance; the amount of extra information that can be thrown out due to its irrelevance. The SCC is in an early stage of its development, however with real data testing and further research, a breakthrough technology is possible.

MN-IP Try and Buy
Try
  • Trial period of 6 to 12 months. $5000/6 months.
  • Fee waived for MN-based companies or if sponsoring $50,000+ in research.
Buy
  • Exclusive license for a $30,000 conversion payment.
  • No patent costs.
  • Royalty rate of 3% (2% for MN company) after first $1 million in product sales.

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** Contact Andrew Morrow for more information.

BENEFITS OF SPECTRAL CURVATURE CLUSTERING

  • Software can be run on virtually any platform
  • Runs with immense speed
  • Can handle large amount of background noise
  • Works best with Hybrid Linear Modeling
  • Provides further analysis for computer-vision based decisions