Vehicles detection in Traffic Flow

Traffic Flow Analysis System is an important part of Intelligent Transportation Systems. It mainly contains two parts: vehicle detection part and vehicle tracking part. The efficient video object segmentation algorithm is the basis of vehicle detection part that aims to segment each vehicle correctly. In this paper, according to the street traffic environment, we adopt a multiple video object segmentation algorithm in vehicle detection. The algorithm consists of training section and segmentation section. At the training section, it uses codebook method to train the vehicle images: First, it uses Scale-invariant feature transform method to extract the features of vehicle image samples. Secondly, it segments the images into small patches to cluster. Third, it uses a new way to activate the codebook that can largely reduce the numbers of vehicle sample images. At the segmentation section, it uses an Implicit Shape Model to combine the recognition knowledge and the segmentation knowledge together. At last, we use this algorithm to implement a prototype of traffic flow analysis system, and achieve the expected results.