Spatiotemporal helixes for modeling environmental data

Spatiotemporal helixes are a new method for modeling the changes an object experiences over time. They have the potential to be used as a predictive tool for geographical and biological applications. We present the formal foundations of these helixes and include experiments to demonstrate their usefulness when data collection is not optimal, such as when noise is present or when there is more than one object of interest present in a single video stream.