Citation

Tan, Wooi Haw and Ooi, Chee Pun and Hammami, Samir Marwan and Alhammami, Muhammad (2019) Optimised ML-based System Model for Adult-Child Actions Recognition. KSII Transactions on Internet and Information Systems, 13 (2). pp. 929-944. ISSN 1976-7277

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Abstract

Many critical applications require accurate real-time human action recognition. However, there are many hurdles associated with capturing and pre-processing image data, calculating features, and classification because they consume significant resources for both storage and computation. To circumvent these hurdles, this paper presents a recognition machine learning (ML) based system model which uses reduced data structure features by projecting real 3D skeleton modality on virtual 2D space. The MMU VAAC dataset is used to test the proposed ML model. The results show a high accuracy rate of 97.88% which is only slightly lower than the accuracy when using the original 3D modality-based features but with a 75% reduction ratio from using RGB modality. These results motivate implementing the proposed recognition model on an embedded system platform in the future.

Item Type:	Article
Uncontrolled Keywords:	Human action recognition, 2D Skeleton features, 3D Projection, Reduced data structure, Compound features selection method
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	17 Feb 2022 01:15
Last Modified:	17 Feb 2022 01:15
URII:	http://shdl.mmu.edu.my/id/eprint/9152

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