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» Randomness and Geometric Features in Computer Vision
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VISSYM
2007
13 years 10 months ago
Parametric Visualization of High Resolution Correlated Multi-spectral Features Using PCA
An imaging mass spectrometer is an analytical instrument that can determine the spatial distribution of chemical compounds on complex surfaces. The output of the device is a multi...
Alexander Broersen, Robert van Liere, Ron M. A. He...
CVPR
2009
IEEE
15 years 2 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
ICCV
2007
IEEE
14 years 9 months ago
Stochastic Adaptive Tracking In A Camera Network
We present a novel stochastic, adaptive strategy for tracking multiple people in a large network of video cameras. Similarities between features (appearance and biometrics) observ...
Bi Song, Amit K. Roy Chowdhury
ICPR
2000
IEEE
14 years 1 days ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
SCALESPACE
2007
Springer
14 years 1 months ago
Non-negative Sparse Modeling of Textures
This paper presents a statistical model for textures that uses a non-negative decomposition on a set of local atoms learned from an exemplar. This model is described by the varianc...
Gabriel Peyré