Abstract:
The extensive growth of the population has resulted in forming uncontrollable
crowds and queues in public places. The Outdoor Patient Departments (OPDs) in
government hospitals are frequently crowded with uncontrolled queues, resulting
in various difficulties for both the patients as well as the staff. Therefore, crowd
detection and counting techniques can be used to find a solution to these issues.
However, the techniques used for detecting crowds vary according to the
circumstances. The focus of this study is to enhance the efficiency of the Patient
Management in OPDs in Government Hospitals, by introducing the application of
crowd detection mechanism to identify and calculate the number of people in
OPDs crowd. This study has focused on developing an effective crowd-detection
technique to be used in OPDs. This will help to diminish the waiting time of
the patients. The count can be used to effectively manage the patients who wait in
queues for hours to get their treatments. There are various existing crowd detection
and counting techniques that can be applied in different application scenarios.
However, these techniques cannot be used to detect the crowd at OPD premises,
which specifically needs a specialized detection technique. This study
comparatively analyses a customized OPD crowd detection technique and evaluates
state-of-the-art methods for detecting the crowd to find the best approach
to count the people at OPD premises. Through this study, a customized crowd
detector was developed and the efficiency of the detector was analyzed. The
accuracy of our custom dataset was analyzed by comparing it with the publicly
available COCO dataset.
