Deep Learning-Based Dynamic Vision: Classifying Hand Gestures

Title

Deep Learning-Based Dynamic Vision: Classifying Hand Gestures

Creator

Sinha, Ayushi; Gunavathi, R.; Johnsan, Amala

Description

In the field of hand gesture recognition, this research introduces novel approaches by utilising a variety of state-of-the-art deep learning models, including YOLOv6, YOLOv8, VGG16, VGG19, and ResNet50. Our work involved rigorous dataset annotation and preprocessing, coupled with custom data augmentation techniques tailored for real-world scenarios. The results were excellent, as YOLOv6 exhibited remarkable precision, achieving an impressive Average Precision (AP) of 97.4% and recall (AR) of 90%. Meanwhile, YOLOv8s prowess shone in specific classes, where it attained a remarkable mean Average Precision (mAP) of 89%. We further explored the capabilities of classical Convolutional Neural Networks (CNNs) such as VGG16 and VGG19. These models demonstrated solid performance with an average accuracy of 74 and 67%, respectively. Our study also explored the utilization of ResNet50, which, despite its popularity in other computer vision tasks, showed a lower accuracy of 33% in the context of hand gesture recognition. This research showcases a significant leap beyond the conventional CNN-based research in hand gesture recognition, as we integrated both object detection and image classification models into the evaluation framework. Looking ahead, our research opens doors to exploring ensemble models that synergize the strengths of YOLOv6, YOLOv8, VGG16, and VGG19, promising a harmonized performance across all classes. Moreover, we advocate for further research into transfer learning techniques, anticipating even higher accuracy levels in scenarios constrained by limited training data. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Source

Lecture Notes in Networks and Systems;Volume;1182;pp.513-526

Date

01-01-2025

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

CNN; Computer vision; Deep learning; Gesture recognition; YOLOv6; YOLOv8

Coverage

Sinha A., Christ Deemed to Be University, Pune, India; Gunavathi R., Christ Deemed to Be University, Pune, India; Johnsan A., Christ Deemed to Be University, Pune, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 23673370; ISBN: 978-981978864-4;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-97-8865-1_42

https://www.scopus.com/pages/publications/105005255393?origin=resultslist