Attention! A Lightweight 2D Hand Pose Estimation Approach

Autor:	Santavas, Nicholas, Kansizoglou, Ioannis, Bampis, Loukas, Karakasis, Evangelos, Gasteratos, Antonios
Rok vydání:	2020
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Human-Computer Interaction Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	Vision based human pose estimation is an non-invasive technology for Human-Computer Interaction (HCI). Direct use of the hand as an input device provides an attractive interaction method, with no need for specialized sensing equipment, such as exoskeletons, gloves etc, but a camera. Traditionally, HCI is employed in various applications spreading in areas including manufacturing, surgery, entertainment industry and architecture, to mention a few. Deployment of vision based human pose estimation algorithms can give a breath of innovation to these applications. In this letter, we present a novel Convolutional Neural Network architecture, reinforced with a Self-Attention module that it can be deployed on an embedded system, due to its lightweight nature, with just 1.9 Million parameters. The source code and qualitative results are publicly available. Comment: updated version with ablation studies
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2001.08047 Zobrazit plný text záznamu View this record from Arxiv