Method and system for achieving classification of pedestrians and vehicles based on neural network

Abstract

The invention relates to the technical field of classification of pedestrians and vehicles, and discloses a method and a system for achieving the classification of pedestrians and vehicles based on a neural network. The method includes the following steps of collecting a plurality of training samples, classifying the training samples by a convolutional neural network, and thereby obtaining a classifier including tab results, when the pedestrians and the vehicles are classified, reading a video image to be detected, detecting moving objects in the image, and processing the image in blocks according to the moving objects; and then classifying the image blocks by the classifier to obtain a detection result; therefore, the neural network system can be simply constructed as the classifier; the system is trained by using different pedestrian and vehicle samples such that the system automatically learns the complex class conditional density of the samples, and problems caused by an artificial hypothesis class conditional density function are avoided. Compared with existing methods for classifying pedestrians and vehicles, the method for achieving the classification of pedestrians and vehicles based on the neural network has the advantages of improving classifying accuracy as well as classifying speed.

Description

technical field [0001] The invention relates to the technical field of vehicle classification, in particular to a method and system for realizing the classification of people and vehicles based on a neural network. Background technique [0002] Traffic accidents are one of the main factors leading to the death of pedestrians. Because cyclists and pedestrians are often in a vulnerable position in traffic accidents, once they have a traffic accident with a motor vehicle, they are easily injured. Therefore, pedestrian detection technology has become a research direction that has attracted much attention in the field of intelligent analysis in recent years. Especially for the field of intelligent traffic video analysis, the classification and detection of objects play a vital role in road management and traffic safety. [0003] At present, the main methods of target classification are methods based on shape model matching, methods based on classifiers and methods using gradient ...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the polymorphism of pedestrians and the diversity of people and vehicles determine that ideal results cannot be achieved through model matching.

[0019] However, the existing classification methods for people and vehicles still have certain deficiencies in the classification accuracy or speed, and the existing technology needs to be improved and improved.

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