Author(s): Adarsh K V, Abhijith A, Adarsh Balan V V, Advait Nikesh, Priya V V

Abstract: Identifying people vulnerable to COVID-19 infections is crucial in stopping the spread of the virus. The key to avoid the fast spreading of virus is to keep social distance. But it becomes difficult to keep distance in public places. Because so many people will visit frequently for full-filling their needs. Counting people and Detecting Humans are important problems in visual surveillance. In recent years, the field has seen many advances, but the solutions have restrictions: people must be moving, the background must be simple, and the image resolution must be high. Main focus of this work is to find methods that effectively deal with the above mentioned real-time issues. Machine Learning algorithms are utilized to identify the individual persons in a video frame. The dataset is thenceforth utilized to analyze the individual persons and count of individual persons are displayed into mobile application. Developing to build an efficient system to avoid rush in institutions, organization and even public places will help people for better time management.