Human Motion Recognition Using Isomap and Dynamic Time Warping

In this paper, we address the problem of recognizing human motion from videos. Human motion recognition is a challenging computer vision problem. In the past ten years, a number of successful approaches based on nonlinear manifold learning have been proposed. However, little attention has been given to the use of isometric feature mapping (Isomap) for human motion recognition. Our contribution in this paper is twofold. First, we demonstrate the applicability of Isomap for dimensionality reduction in human motion recognition. Secondly, we show how an adapted dynamic time warping algorithm (DTW) can be successfully used for matching motion patterns of embedded manifolds. We compare our method to previous works on human motion recognition. Evaluation is performed utilizing an established baseline data set from the web for direct comparison. Finally, our results show that our Isomap-DTW method performs very well for human motion recognition.