Nonlinear dimensionality reduction with hybrid distance for trajectory representation of dynamic texture

DOI10.1016/j.sigpro.2009.12.018zbMath1194.94112OpenAlexW2091504889MaRDI QIDQ985584

Keith C. C. Chan, Yang Liu, Yan Liu

Publication date: 6 August 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2009.12.018

zbMATH Keywords

nonlinear dimensionality reductiondynamic texturehybrid distance isometric embeddingvideo trajectory

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items

Fourier spectral factor model for prediction of multidimensional signals

Uses Software

• darch
• clusfind

Cites Work

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• Dynamic textures
• Hierarchical clustering schemes
• Reducing the Dimensionality of Data with Neural Networks
• Finding Groups in Data
• Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
• Self-organizing maps.