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Publication Detailed Description
ECAI 2016: 22nd European Conference on Artificial Intelligence
Year (definitive publication)
2016
Language
English
Country
Netherlands
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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.
Acknowledgements
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Keywords
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
- Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| SFRH/BDE/52125/2013 | Fundação para a Ciência e a Tecnologia |
Contributions to the Sustainable Development Goals of the United Nations
With the objective to increase the research activity directed towards the achievement of the United Nations 2030 Sustainable Development Goals, the possibility of associating scientific publications with the Sustainable Development Goals is now available in Ciência-IUL. These are the Sustainable Development Goals identified by the author(s) for this publication. For more detailed information on the Sustainable Development Goals, click here.
