Partial matching face recognition method for rehabilitation nursing robots beds

TL;DR

This paper presents a face recognition method based on partial matching Hu moments designed for real-time monitoring of patients in rehabilitation nursing robot beds, demonstrating high accuracy and efficiency.

Contribution

It introduces a novel face recognition approach using Hu moments and partial matching tailored for dynamic environments in healthcare robotics.

Findings

Recognition accuracy of 91%

Average recognition time of 4.3 seconds

Effective in dynamic video scenarios

Abstract

In order to establish face recognition system in rehabilitation nursing robots beds and achieve real-time monitor the patient on the bed. We propose a face recognition method based on partial matching Hu moments which apply for rehabilitation nursing robots beds. Firstly we using Haar classifier to detect human faces automatically in dynamic video frames. Secondly we using Otsu threshold method to extract facial features (eyebrows, eyes, mouth) in the face image and its Hu moments. Finally, we using Hu moment feature set to achieve the automatic face recognition. Experimental results show that this method can efficiently identify face in a dynamic video and it has high practical value (the accuracy rate is 91% and the average recognition time is 4.3s).