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ECCV
2004
Springer
14 years 8 months ago
3D Human Body Tracking Using Deterministic Temporal Motion Models
Abstract. There has been much effort invested in increasing the robustness of human body tracking by incorporating motion models. Most approaches are probabilistic in nature and se...
Raquel Urtasun, Pascal Fua
NIPS
2007
13 years 7 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...
MCS
2008
Springer
13 years 6 months ago
A wildland fire model with data assimilation
A wildfire model is formulated based on balance equations for energy and fuel, where the fuel loss due to combustion corresponds to the fuel reaction rate. The resulting coupled p...
Jan Mandel, Lynn S. Bennethum, Jonathan D. Beezley...
ISVC
2007
Springer
14 years 16 days ago
Gradient-Based Hand Tracking Using Silhouette Data
Optical motion capture can be classified as an inference problem: given the data produced by a set of cameras, the aim is to extract the hidden state, which in this case encodes t...
Paris Kaimakis, Joan Lasenby
ICIP
2005
IEEE
14 years 8 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang