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» Learning and Recognizing Human Dynamics in Video Sequences
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CVPR
2012
IEEE
13 years 1 days ago
Part-based multiple-person tracking with partial occlusion handling
Single camera-based multiple-person tracking is often hindered by difficulties such as occlusion and changes in appearance. In this paper, we address such problems by proposing a...
Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Han...
ICCV
2009
IEEE
1190views Computer Vision» more  ICCV 2009»
16 years 2 months ago
You'll never walk alone: modeling social behavior for multi-target tracking
Object tracking typically relies on a dynamic model to predict the object’s location from its past trajectory. In crowded scenarios a strong dynamic model is particularly impo...
S. Pellegrini, A. Ess, K. Schindler, L. van Gool
IJCV
2008
201views more  IJCV 2008»
14 years 9 months ago
Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation
This paper describes two algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from colour/contr...
Vladimir Kolmogorov, Antonio Criminisi, Andrew Bla...
NIPS
2007
14 years 11 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...
FGR
2008
IEEE
170views Biometrics» more  FGR 2008»
15 years 4 months ago
Using an adaptive VAR Model for motion prediction in 3D hand tracking
A robust VAR-based (vector autoregressive) model is introduced for motion prediction in 3D hand tracking. This dynamic VAR motion model is learned in an online manner. The kinemat...
Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph