An image representation of skeletal data for action recognition using convolutional neural networks
Fecha
2019Language
en
Materia
Resumen
In this paper we present preliminary results of an approach for understanding human actions, based on a novel 2D image representation for 3D skeletal data. More specifically, motion information for human skeletal joints is transformed to a pseudo-colored image. A Convolutional Neural Network is then used for classification. Our approach is evaluated for actions that may be used in an ambient assisted living scenario. © 2019 Association for Computing Machinery.