Techniques Used to Capture Skeletal Information and Their Performance Accuracy: A Literature Review

7 Pages Posted: 30 Nov 2020

See all articles by Palanimeera J

Palanimeera J

Deemed to be University Krishnankoil - Kalasalingam Academy of Research and Education

Ponmozhi K

Deemed to be University Krishnankoil - Kalasalingam Academy of Research and Education

Date Written: November 21, 2020

Abstract

Capture techniques show the skeleton-based movement recognition and hidden advantages of a skeleton, which is an active topic in computer -vision. As a result, there are a lot of impressions in handcraft characteristics and covered works that were carried out for decades based on the found out aspect. However, preceding research on movement recognition, focus on styles that dominate video or RGB facts and present-day evaluations are associated with particular indicative illustrations of skeletal facts or a few traditional performances. The authors collected articles from Elsevier, Scopus, Research portal, and dissertation on skeletal representation for review. 12 documents, studies, and abstracts are identified and reviewed, and many skeleton representations extract techniques that include RGB-D sensor, 3D, video image review, handcrafted features, graph signal processing, res_tcn, geometric modification and optical motion capture system(marker-based system). Several consecutive themes emerged from the study of real-time active action recognition and the structure of human joints, descriptor, and points within the lying group, frequency change, and spatial-temporal representation are also discussed for the measurement of tools and methods.

Keywords: Skeleton representation, RGB-D sensor, 3D, graphic, res_tcn, geometric modification, lying group, optical motion capture system

Suggested Citation

J, Palanimeera and K, Ponmozhi, Techniques Used to Capture Skeletal Information and Their Performance Accuracy: A Literature Review (November 21, 2020). Proceedings of the 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), Available at SSRN: https://ssrn.com/abstract=3734853 or http://dx.doi.org/10.2139/ssrn.3734853

Palanimeera J (Contact Author)

Deemed to be University Krishnankoil - Kalasalingam Academy of Research and Education ( email )

India

Ponmozhi K

Deemed to be University Krishnankoil - Kalasalingam Academy of Research and Education ( email )

India

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
18
Abstract Views
163
PlumX Metrics