Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/23230
Author(s): | Jardim, D. Nunes, L. Dias, M. |
Editor: | Van Harmelen, F., Dignum, V., Dignum, F., Bouquet, P., Fox, M., Kaminka, G. A., and Hüllermeier, E. |
Date: | 2016 |
Title: | Impact of automated action labeling in classification of human actions in RGB-D videos |
Volume: | 285 |
Pages: | 1632 - 1633 |
Event title: | 22nd European Conference on Artificial Intelligence, ECAI 2016 |
ISBN: | 978-1-61499-672-9 |
DOI (Digital Object Identifier): | 10.3233/978-1-61499-672-9-1632 |
Abstract: | For many applications it is important to be able to detect what a human is currently doing. This ability is useful for applications such as surveillance, human computer interfaces, games and healthcare. In order to recognize a human action, the typical approach is to use manually labeled data to perform supervised training. This paper aims to compare the performance of several supervised classifiers trained with manually labeled data versus the same classifiers trained with data automatically labeled. In this paper we propose a framework capable of recognizing human actions using supervised classifiers trained with automatically labeled data in RGB-D videos. |
Peerreviewed: | no |
Access type: | Open Access |
Appears in Collections: | ISTAR-CRI - Comunicações a conferências internacionais |
Files in This Item:
File | Description | Size | Format | |
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conferenceobject_42665.pdf | Versão Editora | 131,13 kB | Adobe PDF | View/Open |
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