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ICCV
2007
IEEE
15 years 11 months ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...
CVPR
2009
IEEE
1216views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Marked Point Processes for Crowd Counting
A Bayesian marked point process (MPP) model is developed to detect and count people in crowded scenes. The model couples a spatial stochastic process governing number and placem...
Robert T. Collins, Weina Ge
PARELEC
2002
IEEE
15 years 2 months ago
Dynamic Process Partitioning and Migration for Irregular Applications
Many practical applications generate irregular, nonbalanced divide-and-conquer trees which have different depths, possibly also different numbers of successors at different levels...
Pawel Czarnul
TIP
2010
121views more  TIP 2010»
14 years 4 months ago
Robust Processing of Optical Flow of Fluids
Abstract--This paper proposes a new approach, coupling physical models and image estimation techniques, for modelling the movement of fluids. The fluid flow is characterized by tur...
Ashish Doshi, Adrian G. Bors
ICIP
2003
IEEE
15 years 11 months ago
Adaptive system on a chip (ASOC): a backbone for power-aware signal processing cores
For motion estimation (ME) and discrete cosine transform (DCT) of MPEG video encoding, content variation and perceptual tolerance in video signals can be exploited to gracefully t...
Andrew Laffely, Jian Liang, Russell Tessier, Wayne...