Implementation of Algorithm of People Counting and Blob Analysis Using OpenCv and Python
Abstract
For the last few
months, the world is suffering from epidemic COVID-19. It is found that till
all people are vaccinated, we all must take the precautionary measures of using
hand sanitizers, face masks and the most important is following social
distancing. Computer vision technology can play a vital role in this crucial
scenario. The advanced video processing algorithms provide fast computational
capability, provides a possibility to use video tracking and counting people in
real-time. The adoption of this measure not only serves as a crisis plan for
pandemic but also provides a range of benefits in long term. In this paper, we
propose an algorithm that analyzes a video sequence detects people to yield
frequency of people along the direction of path traversal which can be
implemented in the open-access building such as malls, airports, shopping
centers, etc. It can be easily integrated into already existing systems if there
are already installed surveillance cameras. The result obtained can be used for
purpose of statistics in the circumstances of any calamity occurrence for the
rescue team to take relevant measures to rescue the people. This paper gives
the solution using blob analysis using Open-CV and python.
Country : India
1 Kurla Kumar Kranthi
Assistant Professor, Department of Computer Science And Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India
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