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» A Bayesian Framework for Multi-cue 3D Object Tracking
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AMDO
2008
Springer
13 years 9 months ago
Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model
Abstract. In this paper we present our work on markerless model-based 3D human motion capture using multiple cameras. We use an industry proven anthropometric human model that was ...
Jan Bandouch, Florian Engstler, Michael Beetz
CVPR
2000
IEEE
13 years 11 months ago
Likelihood Functions and Confidence Bounds for Total-Least-Squares Problems
This paper addresses the derivation of likelihood functions and confidence bounds for problems involving overdetermined linear systems with noise in all measurements, often referr...
Oscar Nestares, David J. Fleet, David J. Heeger

Publication
1500views
15 years 8 months ago
Robust Centerline Extraction Framework Using Level Sets
In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected aut...
M. Sabry Hassouna, Aly A. Farag

Presentation
3660views
15 years 8 months ago
Robust Centerline Extraction Framework Using Level Sets
In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected auto...
M. Sabry Hassouna
ICIP
2009
IEEE
14 years 8 months ago
Robust Visual Tracking Based On Simplified Biologically Inspired Features
We address the problem of robust appearance-based visual tracking. First, a set of simplified biologically inspired features (SBIF) is proposed for object representation and the B...