Citation

Alhammami M, Hammami SM. MethodsX 2021; 8: 101378.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.mex.2021.101378

PMID

34430274

Abstract

We present in this paper an FPGA-based IP for recognizing most common violent actions against children (VACR IP). VACR IP uses only skeleton joints data as inputs to keep the privacy of people inside their homes or in the schools. The proposed hardware achieved a detection rate of 97.72%, processing speed 761FPS, and a latency value equals to 2.79msec using a 50MHz system clock. In sum, this research method presents:•First FPGA-based IP for recognizing most common child abuses without any privacy breach of people real images by using only skeleton joints data.•The IP can detect the violence and the type of the violent action.•The IP can be embedded in complete systems to be installed in schools by school psychologists and counselors.

Language: en

Keywords

Machine learning; Action recognition; Children abuse detection; Fog-based system; FPGA-based hardware IP