A problem in carparks around Auckland is scooter riders dashing in and out of carparks usually to commit an offence. Surveillance cameras cover the entrances to the carparks, but they don’t have automated detection of what is entering or exiting the carpark. This project will look to develop an accurate binary classifier to determine whether an image contains a scooter rider. A range of AI/vision techniques and various parameters could be used to perform the classification. Part of the project will be assessing which approach gives the most accurate identification within a short timeframe and with limited compute resources.
Data: A labelled set of images from carparks is available from the company Kauricone who are looking at ways their classification can be improved.
Undergraduate
A binary classifier which accurately identifies images containing scooters and scooter riders. Perhaps linking to a notification system when a scooter is identified.
Some knowledge of image processing could be beneficial, but this is not a requirement.
Computer Science (303S.499, Lab)