A method for determining the area where traffic targets are located based on traffic video data images

Abstract

The invention relates to a method for determining an area where a traffic target is located based on a traffic video data image. The method is technologically characterized by including the steps of recording a focus point produced when the driver observes a piece of real traffic video, training a traffic target detection template, conducting convolution through the traffic target detection template and the video, extracting out features, based on an object, of the video, extracting motion features of the video through a space-time direction filter, using pixels of an eye focus position as a positive sample, using the pixels of positions except the eye focus position as negative samples, and training a classifier of a support vector machine through a machine learning method according to labels of the samples and features of the samples. Therefore, for any given traffic driving video, object level features and the motion features are inputted into the trained classifier of the support vector machine after being extracted, and the area where the traffic target is located in the traffic driving video can be forecasted.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and relates to a method for determining the area where a traffic target is located based on traffic video data images. Background technique [0002] The study of driver's visual attention is of great significance to reduce traffic accidents, improve driving comfort, study intelligent visual navigation system and interactive load control system. The purpose of studying the driver's visual attention is to determine the area of ​​the traffic target that attracts the driver's attention in the traffic video. Common traffic targets include pedestrians, vehicles, traffic signs, etc. Compared with the method of using expensive high-precision cameras, navigation instruments, sensors and other hardware devices to identify and locate the area where traffic targets are located, algorithms based on computational vision have the advantages of low cost, high intelligence, and easy transplantation. Most...

AI Technical Summary

Problems solved by technology

Although these methods have achieved good results, they also have some insurmountable defects: 1) only a certain kind of traffic target can be identified, and it is impossible to find out all traffic targets that may attract the driver's attention in the entire traffic scene; 2) ) The method is cumbersome and complicated; 3) The guidance of high-level visual cognition is not considered, and it does not conform to the real driver's visual attention distribution

4) Most of them are unsupervised processing methods, which fail to make full use of the already mastered visual features of traffic objects

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