This project consists of two mini projects. Both the mini projects uses HAAR Cascade Classifiers for specific object detection like face, eye, pedestrians and cars.
A Haar Cascade is basically a classifier which is used to detect the object for which it has been trained for, from the source. The Haar Cascade is trained by superimposing the positive image over a set of negative images.
For example- If we are training HAAR cascade for classifying faces then positive images would be the images with human faces in it and negative images would be images without human faces with it.
(Note: Some comment lines are included for better understanding of the code)
This mini project consists of three modules.
- The first module detects human faces from an image fed to it.
- The second module detects eyes from human face.
- The third module is a real time face and eye detection using the system's webcam
This mini project consists of two modules.
- The first module identifies pedestrains walking in the video
- The second module identifies cars.