'High dimension' presentation slideshows

Mean-Field Theory and Its Applications In Computer Vision3

Mean-Field Theory and Its Applications In Computer Vision3. Gaussian Pairwise Potential. Expensive message passing can be performed by cross-bilateral filtering. Spatial. Range. Cross bilateral filter. output. input. output. input. reproduced from [Durand 02].

618 views • 40 slides

Principal Components Analysis (PCA)

Principal Components Analysis (PCA). Principal Components Analysis (PCA). a technique for finding patterns in data of high dimension. Outline: Eigenvectors and eigenvalues PCA: Getting the data Centering the data Obtaining the covariance matrix

546 views • 39 slides

Exploiting Simple Hierarchies for Unsupervised Human Behavior Analysis

Exploiting Simple Hierarchies for Unsupervised Human Behavior Analysis. Fabian Nater Helmut Grabner Luc Van Gool CVPR2010. Abstract. A data-driven, hierarchical approach for the analysis of human actions in visual scenes Completely unsupervised

296 views • 15 slides

225 views • 13 slides

High Dimension

High Dimension. High dimension. SNA. Routes to SNA. SNA to Chaos. PRE, 61, 3641 (2000). Maps. Rossler. Period doubling. Direct Transition:Fixed point to chaos. Riddling to chaos.

209 views • 13 slides

Kernel Density Estimation - concept and applications

Kernel Density Estimation - concept and applications. Bohyung Han bhhan@cs.umd.edu. Kernel Density Estimation. Definition of KDE Characteristics Nonparametric technique Effective multi-modal data representation Consideration of noise for observed data Representation of model/state.

382 views • 10 slides