Title :
Object detection and tracking using the particle filtering
Author :
Lanvin, P. ; Noyer, J.C. ; Benjelloun, M.
Author_Institution :
Lab. d´´Analyse des Systemes du Littoral, Univ. du Littoral Cote d´´Opale, Calais, France
Abstract :
In this paper, we present a method for detecting and tracking rigid moving objects in a monocular image sequence. The originality of this method lies in a state modelling of this estimation problem which is solved in an unified way. This hybrid estimation problem leads to nonlinear state equations that are solved by the particle filtering. A particle filter is set for each shape model (modes). It estimates the motion and position parameters, tracks the object in the sequence and also computes at each time the probability of all modes.
Keywords :
filtering theory; image sequences; motion estimation; nonlinear equations; object detection; tracking; hybrid estimation problem; monocular image sequence; motion-position estimation; nonlinear state equations; object detection; particle filtering; tracking; Application software; Computer vision; Filtering; Motion estimation; Nonlinear equations; Object detection; Particle filters; Particle tracking; Shape; State estimation;
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on
Print_ISBN :
0-7803-8104-1
DOI :
10.1109/ACSSC.2003.1292254
