Online alignment of human motion using forward plotting‐dynamic time warping

A number of approaches to online time warping have been proposed based on plotting an alignment path backwards from a selected end-point. When continually updating a time warp to align a time series with a live data source, such as a stream of motion capture data, the use of backwards plotting makes it hard to maintain a monotonic constraint. To solve this problem, a number of time warping approaches based on forward plotting, referred to as FP-DTW, are proposed and evaluated by applying them to human motions. We demonstrate that forward plotting for temporal alignment is a viable solution when backwards plotting is otherwise not possible