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ICIAP
2009
ACM
14 years 11 months ago
Pathnodes Integration of Standalone Particle Filters for People Tracking on Distributed Surveillance Systems
In this paper, we present a new approach to object tracking based on batteries of particle filter working in multicamera systems with non overlapped fields of view. In each view th...
Roberto Vezzani, Davide Baltieri, Rita Cucchiara
CAIP
2001
Springer
14 years 3 months ago
Tracking People in Sport: Making Use of Partially Controlled Environment
Many different methods for tracking humans were proposed in the past several years, but only a few authors examined the accuracy of the proposed systems. As the accuracy analysis ...
Janez Pers, Stanislav Kovacic
ICIP
2007
IEEE
15 years 17 days 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...
CVPR
2006
IEEE
15 years 27 days ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
ICCV
2005
IEEE
14 years 4 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...