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CVPR
2012
IEEE
11 years 11 months ago
We are not contortionists: Coupled adaptive learning for head and body orientation estimation in surveillance video
In this paper, we deal with the estimation of body and head poses (i.e orientations) in surveillance videos, and we make three main contributions. First, we address this issue as ...
Cheng Chen, Jean-Marc Odobez
MVA
1992
166views Computer Vision» more  MVA 1992»
13 years 10 months ago
Estimation and Interpretation of Optical Flow Fields for Counting Moving Objects
The main goal of sequence analysis is the motion estimation of moving objects which are present in the scene. One of the most important approaches for motion estimation is based o...
Alberto Del Bimbo, Paolo Nesi, Jorge L. C. Sanz
ICPR
2006
IEEE
14 years 10 months ago
Classifiers for Motion
In this paper we present a unsupervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn ...
Mithun Das Gupta, Nemanja Petrovic, ShyamSundar Ra...
ICIP
2005
IEEE
14 years 2 months ago
Higher order polynomials, free form deformations and optical flow estimation
In this paper, we propose a novel technique to represent and recover optical flow through free form deformations. Such a technique is based on representing the motion field usin...
Konstantinos Karantzalos, Nikos Paragios
ICCV
2011
IEEE
13 years 16 days ago
Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling
Human motion capturing (HMC) from multiview image sequences constitutes an extremely difficult problem due to depth and orientation ambiguities and the high dimensionality of the s...
Gerard Pons-Moll, Andreas Baak, Juergen Gall, Laur...