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arXiv · 2001.08047

Attention! A Lightweight 2D Hand Pose Estimation Approach

Nicholas Santavas·Ioannis Kansizoglou·Loukas Bampis·Evangelos Karakasis·Antonios Gasteratos
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Abstract

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.

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Nicholas Santavas, Ioannis Kansizoglou, Loukas Bampis, Evangelos Karakasis, Antonios Gasteratos. 2020-01-22. Attention! A Lightweight 2D Hand Pose Estimation Approach. https://arxiv.org/abs/2001.08047

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