Gesture Recognition in 3D Space Using Dimensionally Reduced Set of Features

Abstract : In this study authors present a solution to track and recognize arbitrary gestures of hands in three dimensional space and review the recognition accuracy. The idea of this novel gesture recognition system is described and results of research made on a recorded gesture data set are presented. Gesture instances were defined by user standing in different distances from the controller, in different placements of their field of vision and with different speeds, making recognition velocity and position invariant. Authors’ goal was to find the minimal number of features that give satisfying gesture classification result in order to achieve a compromise between accuracy and computation time. In this publication progress of the research on gesture recognition problem is described and a comparative study is presented.
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Communication dans un congrès
Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.167-179, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_15〉
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Łukasz Gadomer, Marcin Skoczylas. Gesture Recognition in 3D Space Using Dimensionally Reduced Set of Features. Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.167-179, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_15〉. 〈hal-01656209〉

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