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» Measurement Error Estimation for Feature Tracking
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FGR
2006
IEEE
157views Biometrics» more  FGR 2006»
14 years 2 months ago
Evaluating Error Functions for Robust Active Appearance Models
Active appearance models (AAMs) are generative parametric models commonly used to track faces in video sequences. A limitation of AAMs is they are not robust to occlusion. A recen...
Barry-John Theobald, Iain Matthews, Simon Baker
IVC
2007
187views more  IVC 2007»
13 years 8 months ago
Non-rigid structure from motion using ranklet-based tracking and non-linear optimization
In this paper, we address the problem of estimating the 3D structure and motion of a deformable object given a set of image features tracked automatically throughout a video seque...
Alessio Del Bue, Fabrizio Smeraldi, Lourdes de Aga...
ECCV
2006
Springer
14 years 10 months ago
High Accuracy Optical Flow Serves 3-D Pose Tracking: Exploiting Contour and Flow Based Constraints
Tracking the 3-D pose of an object needs correspondences between 2-D features in the image and their 3-D counterparts in the object model. A large variety of such features has been...
Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-...
AMDO
2008
Springer
13 years 10 months ago
Real-Time 3D Body Pose Tracking from Multiple 2D Images
We present a human body motion tracking system for an interactive virtual simulation training environment. This system captures images using IR illumination and near-IR cameras to ...
Chi-Wei Chu, Ramakant Nevatia
CORR
2010
Springer
166views Education» more  CORR 2010»
13 years 8 months ago
A new closed-loop output error method for parameter identification of robot dynamics
Off-line robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sample...
Maxime Gautier, Alexandre Janot, Pierre-Olivier Va...