Utilizing Skeleton Data for Enhanced Action and Gesture Recognition

Skeleton data from human postures and movements reveals much for enhancing action and gesture detection systems. This study explores methods that optimise data use, improving recognition performance. Our approach uses skeletal data to enable more intuitive and seamless human-machine interactions in healthcare, entertainment, security, and other fields. Computer vision and human-computer interaction benefit from skeleton data. Our research develops novel methods to enhance action and gesture detection systems by utilizing skeletal information. These methods enable AI systems to perceive and interpret human gestures, facilitating more natural and successful interactions. Many applications are possible with this research. Patient monitoring and rehabilitation can benefit from gesture recognition. More immersive virtual reality experiences are possible in entertainment. It improves security surveillance and threat detection. AI and skeletal data can enhance the lives and safety of individuals and communities. This research shows how skeletal data can transform action and gesture recognition. Optimizing data use enables more natural and seamless human-machine interactions across various areas, thereby enhancing the quality of life and safety for individuals and communities.

Authors

Publication Details

Journal
AVE Trends in Intelligent Computer Letters
Published
2025-03-01
DOI
https://doi.org/10.64091/aticl.2025.000092
Primary Topic
Human Pose and Action Recognition
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Utilizing Skeleton Data for Enhanced Action and Gesture Recognition

Gnaneswari Gnanaguru, Sara Sekkate, Edwin Shalom Soji, M. Rehena Sulthana et al.
AVE Trends in Intelligent Computer Letters
Human Pose and Action Recognition
article

Utilizing Skeleton Data for Enhanced Action and Gesture Recognition

Gnaneswari Gnanaguru, Sara Sekkate, Edwin Shalom Soji, M. Rehena Sulthana, C. Christina Angelin
article en

Abstract

Skeleton data from human postures and movements reveals much for enhancing action and gesture detection systems. This study explores methods that optimise data use, improving recognition performance. Our approach uses skeletal data to enable more intuitive and seamless human-machine interactions in healthcare, entertainment, security, and other fields. Computer vision and human-computer interaction benefit from skeleton data. Our research develops novel methods to enhance action and gesture detection systems by utilizing skeletal information. These methods enable AI systems to perceive and interpret human gestures, facilitating more natural and successful interactions. Many applications are possible with this research. Patient monitoring and rehabilitation can benefit from gesture recognition. More immersive virtual reality experiences are possible in entertainment. It improves security surveillance and threat detection. AI and skeletal data can enhance the lives and safety of individuals and communities. This research shows how skeletal data can transform action and gesture recognition. Optimizing data use enables more natural and seamless human-machine interactions across various areas, thereby enhancing the quality of life and safety for individuals and communities.

AVE Trends in Intelligent Computer LettersVol. 1(1)
SRM Institute of Science and Technology, Bharath Institute of Higher Education and Research
Openalex Percentile: Top 78%
Human Pose and Action Recognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Utilizing Skeleton Data for Enhanced Action and Gesture Recognition — Gnaneswari Gnanaguru, Sara Sekkate, et al. · AVE Trends in Intelligent Computer Letters (2025) | TGRS Research Map | TGRS