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» Robust Computer Vision through Kernel Density Estimation
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ACIVS
2005
Springer
15 years 5 months ago
Image De-Quantizing via Enforcing Sparseness in Overcomplete Representations
We describe a method for removing quantization artifacts (de-quantizing) in the image domain, by enforcing a high degree of sparseness in its representation with an overcomplete or...
Luis Mancera, Javier Portilla
BMVC
2010
14 years 9 months ago
Moving Camera Registration for Multiple Camera Setups in Dynamic Scenes
Many practical applications require an accurate knowledge of the extrinsic calibration (i.e., pose) of a moving camera. The existing SLAM and structure-from-motion solutions are n...
Evren Imre, Jean-Yves Guillemaut, Adrian Hilton
CVPR
2011
IEEE
14 years 7 months ago
On analyzing video with very small motions
We characterize a class of videos consisting of very small but potentially complicated motions. We find that in these scenes, linear appearance variations have a direct relations...
Robert Pless, Nathan Jacobs, Michael Dixon, Austin...
CVPR
2008
IEEE
16 years 1 months ago
Particle filtering for registration of 2D and 3D point sets with stochastic dynamics
In this paper, we propose a particle filtering approach for the problem of registering two point sets that differ by a rigid body transformation. Typically, registration algorithm...
Romeil Sandhu, Samuel Dambreville, Allen Tannenbau...
FGR
2000
IEEE
163views Biometrics» more  FGR 2000»
15 years 4 months ago
Tracking Interacting People
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...