An efficient particle filter for color-based tracking in complex scenes

Jesus Martinez-del-Rincon, Carlos Orrite-Urunuela, J. Elias Herrero-Jaraba

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Original languageEnglish
Title of host publication2007 IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages176-181
Number of pages6
ISBN (Print)978-1-4244-1695-0
Publication statusPublished - 2007
EventIEEE Conference on Advanced Video and Signal Based Surveillance - London, United Kingdom
Duration: 05 Sep 200707 Sep 2007

Conference

ConferenceIEEE Conference on Advanced Video and Signal Based Surveillance
CountryUnited Kingdom
CityLondon
Period05/09/200707/09/2007

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing

Cite this

Martinez-del-Rincon, J., Orrite-Urunuela, C., & Elias Herrero-Jaraba, J. (2007). An efficient particle filter for color-based tracking in complex scenes. In 2007 IEEE CONFERENCE ON ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE (pp. 176-181). Institute of Electrical and Electronics Engineers (IEEE).