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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