40 search results - page 6 / 8 » Gibbs Likelihoods for Bayesian Tracking |
EMMCVPR
2011
Springer
12 years 7 months ago
2011
Springer
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
IROS
2008
IEEE
14 years 2 months ago
2008
IEEE
— In order to be truly autonomous, robots that operate in natural, populated environments must have the ability to create a model of these unpredictable dynamic environments and ...
RSS
2007
13 years 9 months ago
2007
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
The Bayesian filtering for recursive state estimation and the shape-based matching methods are two of the most commonly used approaches for target tracking. The Multiple Hypothesi...
ECCV
2000
Springer
14 years 9 months ago
2000
Springer
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...