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» Adaptive object tracking by learning background context
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CVPR
2007
IEEE
15 years 11 months ago
Monocular and Stereo Methods for AAM Learning from Video
The active appearance model (AAM) is a powerful method for modeling deformable visual objects. One of the major drawbacks of the AAM is that it requires a training set of pseudo-d...
Jason Saragih, Roland Göcke
BMCBI
2011
14 years 4 months ago
Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression
Background: When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be ...
John J. Heine, Walker H. Land Jr., Kathleen M. Ega...
PERCOM
2003
ACM
15 years 9 months ago
Steerable Interfaces for Pervasive Computing Spaces
This paper introduces a new class of interactive interfaces that can be moved around to appear on ordinary objects and surfaces anywhere in a space. By dynamically adapting the fo...
Gopal Pingali, Claudio S. Pinhanez, Anthony Levas,...
CVPR
2007
IEEE
15 years 11 months ago
A boosting regression approach to medical anatomy detection
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Shaohua Kevin Zhou, Jinghao Zhou, Dorin Comaniciu
CVPR
2009
IEEE
16 years 4 months ago
Recognition using Regions
This paper presents a unified framework for object detection, segmentation, and classification using regions. Region features are appealing in this context because: (1) they enco...
Chunhui Gu, Joseph J. Lim, Pablo Arbelaez, Jitendr...