Classification of time series data is an important problem with applications in virtually every
scientific endeavor. The large research community working on time series classification has …

Most literature on time series classification assumes that the beginning and ending points of
the pattern of interest can be correctly identified, both during the training phase and later …

Given a video sequence, the task of action recognition is to identify the most similar action
among the action sequences learned by the system. Such human action recognition is …

The gesture recognition using motion capture data and depth sensors has recently drawn
more attention in vision recognition. Currently most systems only classify dataset with a …

In this paper we introduce a novel method for action/movement recognition in motion
capture data. The joints orientation angles and the forward differences of these angles in …

Action and gesture recognition from motion capture and RGB-D camera sequences has
recently emerged as a renowned and challenging research topic. The current methods can …

Much of the vast literature on time series classification makes several assumptions about
data and the algorithm's eventual deployment that are almost certainly unwarranted. For …

Action recognition based on the 3D coordinates of body skeleton joints is an important topic
in computer vision applications and human robot interaction. At present, most 3D data are …

In this paper we present a robust motion recognition framework for both motion capture and
RGB-D sensor data. We extract four different types of features and apply a temporal …

This article describes a novel approach to the modeling of human actions in 3D. The method
we propose is based on a “bag of poses” model that represents human actions as …