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CVPR
1998
IEEE
14 years 10 months ago
Joint Probabilistic Techniques for Tracking Multi-Part Objects
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
Christopher Rasmussen, Gregory D. Hager
ICCV
2007
IEEE
14 years 10 months ago
Stochastic Adaptive Tracking In A Camera Network
We present a novel stochastic, adaptive strategy for tracking multiple people in a large network of video cameras. Similarities between features (appearance and biometrics) observ...
Bi Song, Amit K. Roy Chowdhury
ECCV
2004
Springer
14 years 10 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
ECCV
2000
Springer
14 years 10 months ago
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
ICIP
2007
IEEE
14 years 10 months ago
3D Human Motion Tracking using Manifold Learning
This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
Feng Guo, Gang Qian