Peng, M;
Wang, C;
Chen, T;
(2018)
Attention Based Residual Network for Micro-Gesture Recognition.
In:
Proceedings of the 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018).
(pp. pp. 790-794).
IEEE
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Abstract
Finger micro-gesture recognition is increasingly become an important part of human-computer interaction (HCI) in applications of augmented reality (AR) and virtual reality (VR) technologies. To push the boundary of microgesture recognition, a novel Holoscopic 3D Micro-Gesture Database (HoMG) was established for research purpose. HoMG has an image subset and a video subset. This paper is to demonstrate the result achieved on the image subset for Holoscopic Micro-Gesture Recognition Challenge 2018 (HoMGR 2018). The proposed method utilized the state-of-the-art residual network with an attention-involved design. In every block of the network, an attention branch is added to the output of the last convolution layer. The attention branch is designed to spotlight the finger micro-gesture and reduce the noise introduced from the wrist and background. With an extensive analysis on HoMG, the proposed model achieved a recognition accuracy of 80.5% on the validation set and 82.1% on the testing set.
| Type: | Proceedings paper |
|---|---|
| Title: | Attention Based Residual Network for Micro-Gesture Recognition |
| Event: | 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) |
| Location: | Xian, China |
| Dates: | 15 May 2018 - 19 May 2018 |
| ISBN-13: | 978-1-5386-2335-0 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/FG.2018.00127 |
| Publisher version: | http://dx.doi.org/10.1109/FG.2018.00127 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Image recognition, Testing, Convolution, Training, Gesture recognition, Thumb, finger micro-gesture, residual network, attention |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10054478 |
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