Low-Complexity Hand Gesture Recognition System for Continuous Streams of Digits and Letters
Fecha
2016Language
en
Materia
Resumen
In this paper, we propose a complete gesture recognition framework based on maximum cosine similarity and fast nearest neighbor (NN) techniques, which offers high-recognition accuracy and great computational advantages for three fundamental problems of gesture recognition: 1) isolated recognition; 2) gesture verification; and 3) gesture spotting on continuous data streams. To support our arguments, we provide a thorough evaluation on three large publicly available databases, examining various scenarios, such as noisy environments, limited number of training examples, and time delay in system's response. Our experimental results suggest that this simple NN-based approach is quite accurate for trajectory classification of digits and letters and could become a promising approach for implementations on low-power embedded systems. © 2013 IEEE.
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Gesture recognition technologies for gestural know-how management: Preservation and transmission of expert gestures in wheel throwing pottery
Glushkova A., Manitsaris S. (2015)The acquisition of gestural know-how in manual professions constitutes a real challenge since it passes from master to learner, through a many years long « in person » transmission. However this binding transmission is not ... -
Sparse representations for hand gesture recognition
Poularakis, S.; Tsagkatakis, G.; Tsakalides, P.; Katsavounidis, I. (2013)Dynamic recognition of gestures from video sequences is a challenging task due to the high variability in the characteristics of each gesture with respect to different individuals. In this work, we propose a novel ... -
Real-time arm gesture recognition using 3D skeleton joint data
Paraskevopoulos G., Spyrou E., Sgouropoulos D., Giannakopoulos T., Mylonas P. (2019)In this paper we present an approach towards real-time hand gesture recognition using the Kinect sensor, investigating several machine learning techniques. We propose a novel approach for feature extraction, using measurements ...