Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/92466
Title: | Manipulative Tasks Identification by Learning and Generalizing Hand Motions | Authors: | Faria, Diego R. Martins, Ricardo Filipe Alves Lobo, Jorge Dias, Jorge |
Issue Date: | 2011 | Series/Report no.: | IFIP Advances in Information and Communication Technology; | Volume: | 349 | Abstract: | In this work is proposed an approach to learn patterns and recognize a manipulative task by the extracted features among multiples observations. The diversity of information such as hand motion, fingers flexure and object trajectory are important to represent a manipulative task. By using the relevant features is possible to generate a general form of the signals that represents a specific dataset of trials. The hand motion generalization process is achieved by polynomial regression. Later, given a new observation, it is performed a classification and identification of a task by using the learned features. | URI: | https://hdl.handle.net/10316/92466 | ISBN: | 978-3-642-19169-5 978-3-642-19170-1 |
ISSN: | 1868-4238 1861-2288 |
DOI: | 10.1007/978-3-642-19170-1_19 | Rights: | openAccess |
Appears in Collections: | FCTUC Eng.Electrotécnica - Artigos em Livros de Actas |
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