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» Covariant Derivatives and Vision
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ECCV
2006
Springer
15 years 11 months ago
Geometry and Kinematics with Uncertain Data
Abstract. In Computer Vision applications, one usually has to work with uncertain data. It is therefore important to be able to deal with uncertain geometry and uncertain transform...
Christian Perwass, Christian Gebken, Gerald Sommer
ICPR
2008
IEEE
15 years 11 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
ICARCV
2002
IEEE
172views Robotics» more  ICARCV 2002»
15 years 2 months ago
Incremental map building using an occupancy grid for an autonomous monocular robot
This paper centres on the problem of estimating the location of features in the environment within a map building framework for a mobile robot with a single camera. Most of the ex...
R. Gartshore, A. Aguado, C. Galambos
ECCV
1994
Springer
15 years 11 months ago
Pose refinement of active models using forces in 3D
A new algorithm is described for refining the pose of a model of a rigid object, to conform more accurately to the image structure. Elemental 3D forces are considered to act on the...
Anthony D. Worrall, Geoffrey D. Sullivan, Keith D....
CVPR
2001
IEEE
15 years 11 months ago
Affine Arithmetic Based Estimation of Cue Distributions in Deformable Model Tracking
In this paper we describe a statistical method for the integration of an unlimited number of cues within a deformable model framework. We treat each cue as a random variable, each...
Siome Goldenstein, Christian Vogler, Dimitris N. M...