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Tracking using Flocks of Features, with Application to Assisted Handwashing

This paper describes a method for tracking in the presence of distractors, changes in shape, and occlusions. An object is modeled as a flock of features describing its approximate shape. The ock’ s dynamics keep it spatially localised and moving in concert, but also well distributed across the object being tracked. A recursive Bayesian estimation of the density of the object is approximated with a set of samples. The method is demonstrated on two simple examples, and is applied to an assistive system that tracks the hands and the towel during a handwashing task.