In-Vehicle Occupancy Detection And Classification Using Machine Learning

Occupancy detection is a difficult problem. There are several mechanisms exists for occupancy detection in vehicles, particularly in Automobiles. Now, safety has become an important and necessary aspect of the automobile industry. Airbag became a basic and important safety measure in cars. Even though airbag is a vehicle safety device, it can kill children below 12 years due to its rapid action by the exerting lot of force. This project explains about detecting the number of passengers sitting in the car and then classifying each person whether he/she is a child or an adult by processing the image taken from the camera. So that the deployment of airbags can be avoided near children. Each time car speeds from 0 Kmph to 20 Kmph, occupancy of the car is determined and each one is classified again. We are using widely used technique Haar Cascades, for detection. First, we detect faces and then classify each occupant adult or child.