Developing Human Movement Monitoring System using HAAR Cascade Classifier Algorithm
Yuliadi Erdani, Afaf Fadhil Rifa’i, Agil Calfarera · 2021
Walking speed is widely used as the material for research studies in the health sector, especially for early detection of someone who is healthy or sick. The existence of a monitoring system will greatly help a company to detect the health of its workers early. In this paper, an algorithm for calculating a person’s walking speed is developed. This study uses HAAR Cascade Classifier as pedestrian detection and the process of image processing is performed with the help of the OpenCV library. The test results show that the system successfully detects humans both indoors and outdoors in dim lighting conditions (in the afternoon) and bright (during the day). Based on the test results, the system has successfully detected both single-object and multi-object human objects with accuracy in calculating running speed in the range of 86%.