Detecting lameness using 'Re-sampling Condensation' and 'multi-stream cyclic hidden Markov models'

A system for the tracking and classification of livestock movements is presented. The combined `tracker-classifier' scheme is based on a variant of Isard and Blakes `Condensation' algorithm [Int. J. Comput. Vision (1998) 5] known as `Re-sampling Condensation' in which a second set of samples is taken from each image in the input sequence based on the results of the initial Condensation sampling. This is analogous to a single iteration of a genetic algorithm and serves to incorporate image information in sample location. Re-sampling condensation relies on the variation within the spatial (shape) model being separated into pseudo-independent components (analogous to genes). In the system, a hierarchical spatial model based on a variant of the point distribution model [Proc. Br. Mach. Vision Conf. (1992) 9] is used to model shape variation accurately. Results are presented that show this algorithm gives improved tracking performance, with no computational overhead, over Co...

• Type: Journal
• Year: 2002
• Where: IVC
• Authors: Derek R. Magee, Roger D. Boyle
• Keywords: Condensation, IVC 2002, Model, Re-sampling Condensation