Tracking Many Objects Using Subordinated Condensation
D. Tweed, Andrew D. Calway · 2002
We describe a novel extension to the CONDENSATION algorithm for track-ing multiple objects of the same type. Previous extensions for multiple object tracking do not scale effectively to large numbers of objects. The new ap-proach – subordinated CONDENSATION – deals effectively with arbitrary numbers of objects in an efficient manner, providing a robust means of track-ing individual objects across heavily populated and cluttered scenes. The key innovation is the introduction of bindings (subordination) amongst particles which enables multiple occlusions to be handled in a natural way within the standard CONDENSATION framework. The effectiveness of the approach is demonstrated by tracking multiple animals of the same species in cluttered wildlife footage. 1