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ICPR
2010
IEEE
14 years 9 months ago
Adaptive Motion Model for Human Tracking Using Particle Filter
This paper presents a novel approach to model the complex motion of human using a probabilistic autoregressive moving average model. The parameters of the model are adaptively tun...
Mohammad Hossein Ghaeminia, Amir Hossein Shabani, ...
ICPR
2004
IEEE
16 years 7 days ago
Evaluation of Three Optical Flow-Based Observation Models for Tracking
In this paper, we study the use of optical flow as a characteristic for tracking. We analyze the behavior of three flowbased observation models for particle filter algorithms, and...
José M. Fuertes, Manuel J. Lucena, Nicolas ...
ICPR
2004
IEEE
16 years 7 days ago
Embedding Motion in Model-Based Stochastic Tracking
Jean-Marc Odobez, Daniel Gatica-Perez
BMVC
2000
15 years 15 days ago
A Hierarchical Model of Dynamics for Tracking People with a Single Video Camera
We propose a novel hierarchical model of human dynamics for view independent tracking of the human body in monocular video sequences. The model is trained using real data from a c...
I. A. Karaulova, Peter M. Hall, A. David Marshall
ICIP
2003
IEEE
16 years 23 days ago
An optical flow probabilistic observation model for tracking
In this paper, we define an observation model based on optical flow information to track objects using particle filter algorithms. Although the optical flow information enables us...
Antonio Garrido Carrillo, José M. Fuertes, ...