%0 Conference Proceedings
%T Manipulative Tasks Identification by Learning and Generalizing Hand Motions
%+ University of Coimbra [Portugal] (UC)
%A Faria, Diego, R.
%A Martins, Ricardo
%A Lobo, Jorge
%A Dias, Jorge
%Z Part 6: Robotic Systems - II
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 2nd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS)
%C Costa de Caparica, Portugal
%Y Luis M. Camarinha-Matos
%I Springer
%3 Technological Innovation for Sustainability
%V AICT-349
%P 173-180
%8 2011-02-21
%D 2011
%R 10.1007/978-3-642-19170-1_19
%K Motion Patterns
%K Task Recognition
%K Task Generalization
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 5
%Z WG 5.5
%2 https://inria.hal.science/hal-01566578/document
%2 https://inria.hal.science/hal-01566578/file/978-3-642-19170-1_19_Chapter.pdf
%L hal-01566578
%U https://inria.hal.science/hal-01566578
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-WG5-5
%~ IFIP-DOCEIS
%~ IFIP-AICT-349