عنوان المقالة:نموذج نظام محسّن يعتمد على منهجيات تعلم الآلة لتمييز أفعال البالغين على الأطفال Optimised ML-based System Model for Adult-Child Actions Recognition
Muhammad Alhammami, Samir Marwan Hammami, Chee-Pun Ooi and Wooi-Haw Tan
Abstract
نموذج نظام يعتمد على منهجيات تعلم الآلة لتمييز أفعال البالغين على الأطفال
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.
Publication Date
2/28/2019
Publisher
KSII Transactions on Internet and Information Systems
محمد الحمامي | Muhammad Alhammami | 8091