Introduction
Our team “A-Eye” was awarded the second place of Conestoga 4x4 Challenge (Theme: Solution for Smart Cities and Communities) on 2 March 2018. Our team presented a system that improves the safety of communities by providing live actionable intelligence for vision recognition. It could be used to help identify and find missing children, or identify intruders in a workplace or school setting. [1]
Technologies
- We used the React, Node.js, and MongoDB to provide the service that retrieve recognized images from YOLO object detection and face recognition (OpenCV) to retrieve the plate numbers and compare the faces. Our solution provides the plate number which is recognized using object detection. The object detection was written using the YOLO algorithm with Keras and pre-trained weights from YOLO webpage.
Click image to watch the video
Face recognition is implemented by using OpenCV face recognition.
Demonstration
Click image to watch the video
Click image to watch the video
Reference
[1] Conestoga College. (2018, March 5). Students develop smart city solutions at Conestoga competition [Blog post]. retrieved from http://blogs1.conestogac.on.ca/news/2018/03/students_develop_smart_city_so.php