DefinePK

Abstract

Human activity recognition research is an active area in an early stage of development. We present two approaches to activity recognition based on symbolic representations of multivariate time series of joint locations in articulated skeletons. One approach uses pair wise alignment and nearest-neighbor classification, and the other uses spectrum kernels and SVMs as classifiers. We tested both approaches on three datasets derived from RGBD cameras (e.g., Microsoft Kinect) as well as ordinary video, and compared our results with those of other researchers.