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» Unsupervised Learning of Invariant Features Using Video
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PCI
2005
Springer
14 years 1 months ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
CVPR
2004
IEEE
14 years 9 months ago
An Unsupervised, Online Learning Framework for Moving Object Detection
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
Vinod Nair, James J. Clark
EVENT
2001
267views more  EVENT 2001»
13 years 9 months ago
View-Invariant Representation and Learning of Human Action
Automatically understanding human actions from video sequences is a very challenging problem. This involves the extraction of relevant visual information from a video sequence, re...
Cen Rao, Mubarak Shah
ICIP
2008
IEEE
14 years 9 months ago
Learning action dictionaries from video
Summarizing the contents of a video containing human activities is an important problem in computer vision and has important applications in automated surveillance systems. Summar...
Pavan K. Turaga, Rama Chellappa
ICCV
2007
IEEE
14 years 9 months ago
An Invariant Large Margin Nearest Neighbour Classifier
The k-nearest neighbour (kNN) rule is a simple and effective method for multi-way classification that is much used in Computer Vision. However, its performance depends heavily on ...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...