Description

ABSTRACT

Computer Vision and Internet of thing (IOT) is the emerging technologies now a days. To reduce the man power for security aspects in this project a Face Tracking system has been implemented using a single board computer i.e. Raspberry Pi 3 which will act as the CPU in which we will do the coding part using Python and a module named Open Source Computer Vision (OpenCV). A USB camera is attached to the raspberry pi which will be used for face tracking whenever the person come before the camera it will track the face of the person, the main advantage of this is it can track multiple faces at the same time in the single frame. This system make our work easier to track a face where we don’t have to manually track that. OpenCV with python make this system more accurate and easy to track any face. When a person face is tracked in the camera it will give the alert to maintain security especially in the areas where persons are not allowed. The alert is given using the Twilio API which will automatically send the message to the owner when even a face is tracked and detected. 

INTRODUCTION

This system make our work easy to track a person face using the OpenCV with python using a USB camera attached to the raspberry pi. Which will automatically track the face whenever the person is in the frame. Also its advantage is that it can go with more faces at the same time.

EXISTING SYSTEM

In the existing system, the face is tracked by using the captured videos and observing the video continuously to know the status, and to track the person. More time taking part no automation. 

PROPOSED SYSTEM

In this proposed system, the person face is tracked automatically using computer vision which is more accurate and automatic when compared to the previous methods of face tracking. SMS API using Twilio cloud make more automatic as it gives the message automatically when the person is tracked. 

BLOCK DIAGRAM

MONITORING SECTION

BLOCK DIAGRAM EXPLANATION

• In this project USB Camera is connected to the raspberry pi.
• USB Camera acts as the computer vision.
• Connect power supply for Raspberry pi
• Plug the HDMI cable in Raspberry pi from the monitor using VGA to HDMI converter cable
• Connect USB Mouse and USB keyboard to the Raspberry pi
• In the Monitoring section when the face detected automatically SMS is being send. 

HARDWARE REQUIREMENTS

• Raspberry Pi
• USB Camera
• SD card
• Monitor 

SOFTWARE REQUIREMENTS

• Raspbian Jessie
• Language – Linux
• Python
• OpenCV

CONCLUSION

In this system face tracking is made easier by using OpenCV with python, which will track the person face and also intimate using the SMS API with tracking the person in real time surveillance. At the same time more than two persons are also tracked using this system. 

REFERENCES

[1] “A contour based procedure for face detection and tracking from video” in 2016 3rd International Conference on Recent Advances in Information Technology (RAIT)

[2] “An integrated robust approach for fast face tracking in noisy real-world videos with visual constraints” in 2017 International Conference on Intelligent Computing and Control (I2C2) 

[3] MR Sunitha, HS Jayanna, Ramegowda, “Tracking Multiple Moving Object Based on Combined Color and Centroid Feature in Video Sequence”, Proc. of IEEE International Conference on Computational Intelligence and Computing Research, pp. 846-850, 2014