Accurate Hand Gesture Recognition Using Color and Depth Images with Modality-invariant Fusion

Gesture recognition is actively used, and has been applied in various fields, including games and medicine. For accurate gesture recognition, multi-modal information with color and depth images has recently been used. In multimodal gesture recognition, the fusion of color and depth images is crucial...

Full description

Saved in:
Bibliographic Details
Published in2022 IEEE 11th Global Conference on Consumer Electronics (GCCE) pp. 645 - 648
Main Authors Okano, Masaya, Liu, Jia-Qing, Tateyama, Tomoko, Iwamoto, Yutaro, Chen, Yen-Wei
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.10.2022
Subjects
Consumer electronics
Early Fusion
Games
Gesture recognition
Image color analysis
Late Fusion
Modality-invariant Fusion
Multi-model Gesture Recognition
Online AccessGet full text

Cover

More Information
Summary:Gesture recognition is actively used, and has been applied in various fields, including games and medicine. For accurate gesture recognition, multi-modal information with color and depth images has recently been used. In multimodal gesture recognition, the fusion of color and depth images is crucial. To date, early and late fusion approaches have been widely used for the fusion of color and depth images. However, the enhancement of performance is limited due to the gap between the modalities. In this study, we proposed a modality-invariant fusion approach to overcome the modality gap issue. We applied the proposed approach to a public and our private data set and verified its effectiveness.
DOI:10.1109/GCCE56475.2022.10014261