Application of the particle filter to tracking of fish in aquaculture research

Abstract

The analysis of fish movement as an indicator of fish behaviour plays an important role in aquaculture research. Currently observations are carried out manually using video recordings. In this paper we describe a tracking system which can automatically detect and track two fish in a video sequence in a small aquaculture tank. The system is based on the particle filter tracking algorithm augmented by an adaptive partition scheme and using a Global Nearest Neighbour approach for data association. Results show that this method is sufficient for simple interactions where fish bypass each other without significant changes in velocity. However, more complex scenarios involving occlusions, loss of tracks and fish manoeuvres can cause ambiguity during data association.

Available Versions of this Item

• Application of the particle filter to tracking of fish in aquaculture research. (deposited 17 Sep 2008 08:29)
  • Application of the particle filter to tracking of fish in aquaculture research. (deposited 02 Oct 2008 09:21) [Currently Displayed]
    • Application of the particle filter to tracking of fish in aquaculture research. (deposited 20 Jan 2009 12:22)