MIFD-Net : a hand gesture recognition model based on feature fusion of MLP and CNN

Tong Wang; Ge Song; WeiJian Ni; QingTian Zeng

doi:10.1117/12.2655882

12 January 2023 MIFD-Net : a hand gesture recognition model based on feature fusion of MLP and CNN

Tong Wang, Ge Song, WeiJian Ni, QingTian Zeng

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250905 (2023) https://doi.org/10.1117/12.2655882
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

Gesture recognition can play a crucial role in addressing the issue of Human-computer interaction. In this paper, we proposed a vision-based Multi-input fusion deep network (MIFD-Net), which consists of Multilayer Perceptron (MLP) and Convolutional Neural Networks (CNN). MIFD-Net first processes hand keypoint data and gesture images using Euclidean distance normalization (ED-Normalization) and image segmentation technologies, respectively. Then, two kinds of data are simultaneously used as input to MIFD-Net. The experimental results show that the MIFD-Net achieves an average accuracy of 99.65% on the self-built dataset in this paper and 99.10% on the NUS hand posture datasets II (NUS-II). The MIFD-Net significantly decreases its FLOPs and the number of parameters and reduces the complexity of the model while maintaining a high recognition rate compared with other gesture recognition models. The MIFD-Net can obtain high accuracy and strong robustness in different environments, lighting, and angles.

Citation Download Citation

Tong Wang, Ge Song, WeiJian Ni, and QingTian Zeng "MIFD-Net : a hand gesture recognition model based on feature fusion of MLP and CNN", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250905 (12 January 2023); https://doi.org/10.1117/12.2655882

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KEYWORDS

Gesture recognition

Data modeling

Image segmentation

Feature extraction

Data processing

Visual process modeling

Cameras

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