Abstract:
Usage of 3th dimension information obtained from depth sensors in human action recognition has gained importance in the recent years. In this study, basic human actions a...Show MoreMetadata
Abstract:
Usage of 3th dimension information obtained from depth sensors in human action recognition has gained importance in the recent years. In this study, basic human actions are tried to recognize on a human model derived from RGBD sensor. Joint angles and joint displacements used as time series and feature extraction from times series is applied to recognize actions. Actions are classified with the random forest and support vector machine approaches and classification accuracy is measured on MSRAction-3D and MSRC-12 datasets.
Date of Conference: 23-25 April 2014
Date Added to IEEE Xplore: 12 June 2014
Electronic ISBN:978-1-4799-4874-1
Print ISSN: 2165-0608