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» People Tracking with the Laplacian Eigenmaps Latent Variable...
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NIPS
2007
10 years 1 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...
ICIP
2007
IEEE
11 years 1 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
ICCV
2005
IEEE
10 years 5 months ago
Priors for People Tracking from Small Training Sets
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...
CVPR
2008
IEEE
11 years 1 months ago
People-tracking-by-detection and people-detection-by-tracking
Both detection and tracking people are challenging problems, especially in complex real world scenes that commonly involve multiple people, complicated occlusions, and cluttered o...
Mykhaylo Andriluka, Stefan Roth, Bernt Schiele
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