Video tracking system optimization using evolution strategies

Jesús García, Oscar Pérez*, Antonio Berlanga, José M. Molina

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


A video-based tracking system for airport surveillance, composed by modules performing vision tasks at different levels, is adapted for operational conditions by means of Evolution Strategies (ES). An optimization procedure has been carried out considering different scenes composed of representative trajectories, supported by a global evaluation metric proposed to quantify the system performance. The generalization problem (the search of appropriate solutions for general situations, avoiding over-adaptation to particular conditions) is approached considering evaluation of ES-individuals over combinations of trajectories to build the fitness function. In this way, the optimization procedure covers sets of trajectories representing different types of problems. Besides, alternative operators for aggregating partial evaluations have been analysed. Results show how the optimization strategy provides a sensitive tuning of performance related to input parameters at different levels, and how the combination of different situations improves the generalization capability of the trained system. The global performance final system after optimization is also compared with representative algorithms in the state of the art of visual tracking.

Original languageEnglish
Pages (from-to)75-90
Number of pages16
JournalInternational Journal of Imaging Systems and Technology
Issue number2
Publication statusPublished - 2007
Externally publishedYes


  • Learning
  • Optimization
  • Surveillance systems
  • Tracking
  • Video


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