Hand Gesture Recognition with Deep Convolutional Neural Networks: A Comparative Study

You Li Chong, Chin Poo Lee, Kian Ming Lim, Jit Yan Lim

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

Hand gesture recognition is a growing field with applications in human-computer interaction, sign language interpretation, and virtual/augmented reality. The use of convolutional neural networks (CNNs) has become prevalent in this field as they possess the capability to autonomously extract relevant features from image data, facilitating precise and effective hand gesture recognition. This paper presents a comparison of popular pretrained CNN models for hand gesture recognition, evaluating their performance on three widely used datasets: the American Sign Language (ASL) dataset, ASL with Digits dataset, and NUS Hand Posture dataset. The models were fine-tuned and tested, and the analysis included accuracy, training epoch, and training time. The pretrained CNN models compared include VGG16, ResNet50, InceptionV3, DenseNet201, MobileNetV2, Inception ResNetV2, Xception, and ResNet50V2. The findings of this research can provide valuable insights into choosing an appropriate pretrained CNN model for applications involving hand gesture recognition.

Original languageEnglish
Title of host publication2023 IEEE 11th Conference on Systems, Process and Control, ICSPC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages60-65
Number of pages6
ISBN (Electronic)9798350340860
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event11th IEEE Conference on Systems, Process and Control, ICSPC 2023 - Malacca, Malaysia
Duration: 16 Dec 2023 → …

Publication series

Name2023 IEEE 11th Conference on Systems, Process and Control, ICSPC 2023 - Proceedings

Conference

Conference11th IEEE Conference on Systems, Process and Control, ICSPC 2023
Country/TerritoryMalaysia
CityMalacca
Period16/12/23 → …

Keywords

  • Convolution Neural Network (CNN)
  • Sign Language Recognition
  • Static Hand Gesture Recognition
  • Transfer Learning

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