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ICIP
2010
IEEE
14 years 10 months ago
Collaborative particle filters for group tracking
Tracking groups of people is a highly informative task in surveillance, and it represents a still open and little explored issue. In this paper, we propose a brand new framework f...
Loris Bazzani, Marco Cristani, Vittorio Murino
121
Voted
ICPR
2010
IEEE
14 years 10 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, ...
87
Voted
SIBGRAPI
2007
IEEE
15 years 6 months ago
Multiple Mice Tracking using a Combination of Particle Filter and K-Means
This paper presents a new approach to multiple objects tracking that combines particle filters and k-means. The approach has been tested under an important real world situation, ...
Wesley Nunes Gonçalves, João Bosco O...
114
Voted
IBPRIA
2005
Springer
15 years 6 months ago
Probabilistic Image-Based Tracking: Improving Particle Filtering
Condensation is a widely-used tracking algorithm based on particle filters. Although some results have been achieved, it has several unpleasant behaviours. In this paper, we highl...
Daniel Rowe, Ignasi Rius, Jordi Gonzàlez, F...
73
Voted
ICASSP
2011
IEEE
14 years 4 months ago
A mode preserving particle filter
A new particle filtering technique is proposed which addresses the problem of mode preservation in the approximation of multi-modal posteriors. The key is a resampling step which...
Mark R. Morelande, Alan M. Zhang