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CVPR
2011
IEEE
14 years 5 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell
IJON
2006
85views more  IJON 2006»
14 years 9 months ago
From outliers to prototypes: Ordering data
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
ENC
2004
IEEE
15 years 1 months ago
Feature Selection for Visual Gesture Recognition Using Hidden Markov Models
Hidden Markov models have become the preferred technique for visual recognition of human gestures. However, the recognition rate depends on the set of visual features used, and al...
José Antonio Montero, Luis Enrique Sucar
ICPR
2008
IEEE
15 years 11 months ago
Object detection at multiple scales improves accuracy
For detecting objects in natural visual scenes, several powerful image features have been proposed which can collectively be described as spatial histograms of oriented energy. Th...
Stanley M. Bileschi
ICCV
2009
IEEE
1363views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Human Detection Using Partial Least Squares Analysis
Significant research has been devoted to detecting people in images and videos. In this paper we describe a human detection method that augments widely used edge-based features ...
William Robson Schwartz, Aniruddha Kembhavi, David...