Clemente, Mark Angelo L. <br/><br/>
Vision-Based Detection and Physical Distancing Monitoring System / 
Mark Angello L. Clemente, Lemeuel John Crisostomo, Jhelvee De Galicia, Glenn Xavier Magno. 
 - xi, 90 pages :  illustrations ;  28 cm. +  1 CD-ROM (4 3/4 in.) 
<br/><br/> Thesis (Undergraduate) 
<br/><br/>College of Science --<br/> 
<br/><br/>Includes bibliographical references. 
<br/><br/> The study Vision-Based Detection and Physical Distancing Monitoring System encompasses the development of a system that monitors the physical distancing protocol which is designed and aimed to compute the given distance in order to detect and recognize the violators and non-violators of the specific mass covered by the video capturing device.<br/>The system was developed with use of the software tools as Visual Studio Code, and Python Programming Language. YoloV3, the real-time detection model, is also used in training and deploying the model for object detection. For the evaluation of the system, the researchers conducted online surveys using ISO 25010 in the form of an online digital questionnaire, wherein the overall percentage frequency was 66.46% and was interpreted as "Highly Acceptable" from the thirty (30) respondents. The developed system is meant to provide aid to frontline workers who are in patrol implementing the basic health protocols.--Author's Abstract. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Physical distancing.<br/>Social distancing.
<br/><br/><label>LC Class. No.: </label>BTH QA 76  / C54 2022