A Particle Swarm Optimization inspired tracker applied to visual tracking - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

A Particle Swarm Optimization inspired tracker applied to visual tracking

Résumé

Visual tracking is dynamic optimization where time and object state simultaneously influence the problem. In this paper, we intend to show that we built a tracker from an evolutionary optimization approach, the PSO (Particle Swarm optimization) algorithm. We demonstrated that an extension of the original algorithm where system dynamics is explicitly taken into consideration, it can perform an efficient tracking. This tracker is also shown to outperform SIR (Sampling Importance Resampling) algorithm with random walk and constant velocity model, as well as a previously PSO inspired tracker, SPSO (Sequential Particle Swarm Optimization). Experiments were performed both on simulated data and real visual RGB-D information. Our PSO inspired tracker can be a very effective and robust alternative for visual tracking.
Fichier principal
Vignette du fichier
mollaret_15190.pdf (363.7 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01390848 , version 1 (02-11-2016)

Identifiants

Citer

Christophe Mollaret, Frédéric Lerasle, Isabelle Ferrané, Julien Pinquier. A Particle Swarm Optimization inspired tracker applied to visual tracking. IEEE International Conference on Image Processing (ICIP 2014), Oct 2014, Paris, France. pp.426-430, ⟨10.1109/ICIP.2014.7025085⟩. ⟨hal-01390848⟩
291 Consultations
417 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More