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» Robust Incremental Subspace Learning for Object Tracking
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CVPR
2010
IEEE
13 years 7 months ago
A probabilistic framework for joint segmentation and tracking
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
Chad Aeschliman, Johnny Park, Avinash C. Kak
NIPS
2003
13 years 8 months ago
Learning Non-Rigid 3D Shape from 2D Motion
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
14 years 1 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
ICPR
2010
IEEE
13 years 10 months ago
The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking
This work introduces a new pattern recognition model for segmenting and tracking lip contours in video sequences. We formulate the problem as a general nonrigid object tracking me...
Gustavo Carneiro, Jacinto Nascimento
ICPR
2006
IEEE
14 years 8 months ago
Recognizing Facial Expressions by Tracking Feature Shapes
Reliable facial expression recognition by machine is still a challenging task. We propose a framework to recognise various expressions by tracking facial features. Our method uses...
Atul Kanaujia, Dimitris N. Metaxas