Single and multiple target tracking via hybrid mean shift/particle filter algorithms
Naeem, Asad (2010) Single and multiple target tracking via hybrid mean shift/particle filter algorithms. PhD thesis, University of Nottingham.
This thesis is concerned with single and multiple target visual tracking algorithms and their application in the real world. While they are both powerful and general, one of the main challenges of tracking using particle filter-based algorithms is to manage the particle spread. Too wide a spread leads to dispersal of particles onto clutter, but limited spread may lead to difficulty when fast-moving objects and/or high-speed camera motion throw trackers away from their target(s). This thesis addresses the particle spread management problem. Three novel tracking algorithms are presented, each of which combines particle filtering and Kernel Mean Shift methods to produce more robust and accurate tracking.
Actions (Archive Staff Only)