OS6-7 Deep Learning Based Infant and Child Monitoring System

Title:	OS6-7 Deep Learning Based Infant and Child Monitoring System
Publication:	ICAROB2025
Volume:	30
Pages:	179-182
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2025.OS6-7
Author(s):	Peng Wang, Jiale Jia
Publication Date:	February 13, 2025
Keywords:	Deep learning, Neural network, Attribute recognition, Yolov8
Abstract:	This paper focuses on a baby monitoring system based on computer vision and multi-branch convolutional neural network, firstly, the collected photos are processed, and then the algorithm is implemented using openCV library to train to get the baby's facial target detection model, and secondly, based on the opencv algorithm and yolov8 algorithm technology to achieve the tracking and analysis of baby's behavioral trajectory and facial detection. Finally, we realized the functions of target tracking, night lightening, image segmentation and baby face detection, and the detection achieved good results.
PDF File:	https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS6/OS6-7.pdf
Copyright:	© The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/