A model for fine-grained vehicle classification based on deep learning

Abstract

A model for fine-grained vehicle classification based on deep learning is proposed to handle complicated transportation scene. This model comprises of two parts, vehicle detection model and vehicle fine-grained detection and classification model. Faster R-CNN method is adopted in vehicle detection model to extract single vehicle images from an image with clutter background which may contains serval vehicles. This step provides data for the next classification model. In vehicle fine-grained classification model, an image contains only one vehicle is fed into a CNN model to produce a feature, then a joint bayesian network is used to implement the fine-grained classification process. Experiments show that vehicle’s make and model can be recognized from transportation images effectively by using our method. Furthermore,in order to build a large scale database easier, this paper comes up with a novel network collaborative annotation mechanism.