Multiple Mice Tracking using a Combination of Particle Filter and K-Means

13 years 10 months ago

Download sibgrapi.sid.inpe.br

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, related to pharmacological development, which has also proved to serve as an interesting ground-truth dataset provider for the evaluation of tracking algorithms. The obtained results are then compared to other models. The promising results of these experiments are presented.

Wesley Nunes Gonçalves, João Bosco O

Real-time Traffic

Combines Particle ﬁlters | Computer Graphics | Interesting Ground-truth Dataset | Real World Situation | SIBGRAPI 2007 |

claim paper

» A combination of particle filtering and deterministic approaches for multiple kernel track...

» A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking

» Probabilistic Object Tracking Using Multiple Features

» Probabilistic Fusion Tracking Using Mixture KernelBased Bayesian Filtering

» People Tracking with Anonymous and IDSensors Using RaoBlackwellised Particle Filters

» Multimodal tracking using texture changes

» Integrating robust likelihoods with MonteCarlo filters for multitarget tracking

» An AudioVisual Particle Filter for Speaker Tracking on the CLEAR06 Evaluation Dataset

Post Info
More Details (n/a)

Added	04 Jun 2010
Updated	04 Jun 2010
Type	Conference
Year	2007
Where	SIBGRAPI
Authors	Wesley Nunes Gonçalves, João Bosco Oliveira Monteiro, Jonathan de Andrade Silva, Bruno Brandoli Machado, Hemerson Pistori, Valguima Odakura

Comments (0)

Sciweavers

Multiple Mice Tracking using a Combination of Particle Filter and K-Means

Combines Particle ﬁlters | Computer Graphics | Interesting Ground-truth Dataset | Real World Situation | SIBGRAPI 2007 |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers