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JACIII Vol.29 No.1 pp. 95-105
doi: 10.20965/jaciii.2025.p0095
(2025)

Research Paper:

An Ensemble Approach with Evolutionary Algorithm for Hand Posture Classification

Takenori Obo*,† ORCID Icon, Eri Sato-Shimokawara* ORCID Icon, Hiroki Shibata* ORCID Icon, Yihsin Ho** ORCID Icon, and Ichiro Kobayashi** ORCID Icon

*Tokyo Metropolitan University
6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan

Corresponding author

**Takushoku University
815-1 Tatemachi, Hachioji, Tokyo 193-0985, Japan

Received:
June 5, 2024
Accepted:
October 28, 2024
Published:
January 20, 2025
Keywords:
hand pose estimation, ensemble learning, extreme learning machine, genetic algorithm, cross-cultural understanding
Abstract

Grasping is a fundamental action in daily life and particularly evident during mealtime situations where various grasping actions occur with tableware such as chopsticks, spoons, forks, bowls, and cups, each serving specific purposes. While tableware usage varies across regions and cultures, recognizing grasping actions is crucial for assessing performance in daily activities. In this study, we focus on assessing grasping functionality in terms of tableware usage during meals and propose a method for identifying hand movements. In recent years, there has been a surge in developing approaches for hand pose estimation and gesture recognition using deep learning. However, these approaches encounter common challenges, including the need for large-scale datasets, hyperparameter tuning, significant time and computational costs, and limited applicability to incremental learning. To address these challenges, we propose an ensemble approach employing extreme learning machines to recognize grasp postures. In addition, we apply spatiotemporal modeling to extract the relationship between grasp postures and the surrounding tools during mealtimes.

Overview of the proposed ensemble approach forhand posture classification

Overview of the proposed ensemble approach forhand posture classification

Cite this article as:
T. Obo, E. Sato-Shimokawara, H. Shibata, Y. Ho, and I. Kobayashi, “An Ensemble Approach with Evolutionary Algorithm for Hand Posture Classification,” J. Adv. Comput. Intell. Intell. Inform., Vol.29 No.1, pp. 95-105, 2025.
Data files:
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Last updated on Feb. 07, 2025