Convolutional neural network system for object detection and lane detection in a motor vehicle

A system for predicting object detection and lane detection for a motor vehicle, the system comprising:

• a camera mounted to the motor vehicle, the camera capturing an input image having an object, a left lane marking, and a right lane marking;
• a convolution neural network (CNN) receiving the input image, the CNN having:
• a set of convolution and pooling layers (CPL's) trained to detect the object, the left lane marking, and the right lane marking from the input image, wherein the object is categorized into an object class, the left lane marking is categorized into a left lane marking class, and the right lane marking is categorized into a right lane marking class, the CPL's generating a number of feature maps;
• a fully connected layer that receives the feature maps, the fully connected layer generating multiple object bounding box predictions for each of the object classes and multiple lane bounding box predictions for the left lane marking class and the right lane marking class from the feature maps;
• a non-maximum suppression layer receiving the multiple object bounding box predictions and the multiple lane bounding box predictions and generating a final object bounding box prediction for the object class and generating multiple final lane bounding box predictions for each of the lane marking classes;
• and
• a lane line module configured to generate lane lines from the multiple final lane bounding box predictions.