Front camera perception

This project implements an Object classification and localization software module in traffic for Cars, Trucks, Motorcycles Bicycles and Pedestrians using a Mono Camera mounted in the windshield.

Initial Situation

 

Goal of the project was to implement an Object classification and localization software module in traffic for Cars, Trucks, Motorcycles Bicycles and Pedestrians using a Mono Camera mounted in the windshield.

Requirements:

  • Runtime >10 FPS
  • Accuracy >95% TP in ego lane
  • Object: 2-wheelers, Person, Truck, Car

 

Figure 1: Object detection in front camera

Solution

 

We adapted a state-of-the-art CNN and retrained the deeep learning network with an extended dataset. Various tests were realized to validate the accuracy of the targeted requirement. The object detector detects reliably the targeted objects in challenging scenarios such as crowded scenes and low light conditions.