ResNet+LSTM-based gesture recognition method for elderly care robots

Meng Lv

doi:10.1117/12.3008065

14 November 2023 ResNet+LSTM-based gesture recognition method for elderly care robots

Meng Lv

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129340S (2023) https://doi.org/10.1117/12.3008065
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

The incorporation of human-computer interaction technology into senior care robots in recent years has pushed the development of HCI technology in a more compassionate direction, with gesture interaction being the emphasis of research in this area. This paper analyzes the usage of a gesture recognition system based on ResNet+LSTM on an elderly care robot that is challenging to comprehend due to poor gesture detection accuracy, misjudgment, and gesture interaction intention. The process begins with the creation of a gesture dataset, followed by the extraction of gesture features using ResNet, the training of a neural network model using LSTM, and lastly the application of the trained model to the Pepper robot for algorithm evaluation and verification. According to the testing findings, the algorithm significantly improves the aging care robot's ability to recognize gestures.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Meng Lv "ResNet+LSTM-based gesture recognition method for elderly care robots", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129340S (14 November 2023); https://doi.org/10.1117/12.3008065

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KEYWORDS

Gesture recognition

Robots

Education and training

Data modeling

Human computer interaction

Neural networks

Feature extraction

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