Mobile Net SSD Based Face Mask Detection and Crowd Monitoring Using Python Open CV
1Prof.Mayank Mangal, 2Aparna Temkar, 3Pratiksha Keluskar, 4Pragati Bhoir
1 Assistant Professor, Department of Computer Engineering, Alamuri Ratnamala Institute of Engineering and Technology
2,3,4 Student, Department of Computer Engineering, Alamuri Ratnamala Institute of Engineering and Technology
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - In 2020 covid become the biggest threat to the whole world. It started affecting people’s day to day life. many people lost their love ones in these years. Thus, the emphasis is on taking extensive precautions such as social distancing, wearing a mask and using sanitizer etc. which is great for everyone’s health but taking care of this that others are following this precautions or rules in public places are difficult to do manually and to overcome the problem we can use system who has mask detection and people counting program. Which requires more processing because we work with real time video, so our technique is to transform a color image into binary for diminish the data of image. In this proposed system commuting processing time is an necessary part to build a powerful effective working system. Checking whether the people wearing a mask or not and then counting a peoples based on head detection and evaluating that count of people to system is basic goal. There are four important features in this proposed system mask detection, crowd counting, alarm alert and scan ID. The main features are mask detection and people counting. A technique for mask detection uses three different steps estimating eye line, facial part, and eye detection is used in this system. Alarm alert is used to alert the peoples who are not wearing mask or wearing a mask improperly in the public places.
Key Words: Convolution Neural Network , MobileNet SSD, Dataset
