Vehicle detection method based on convolutional neural network self-adaption

Abstract

The present invention discloses a vehicle detection method based on convolutional neural network self-adaption. The method comprises an off-line training step S1 of collecting a vehicle sample and a non-vehicle sample, forming a source sample, carrying out the pre-processing on the source sample and training a source CNN vehicle detector; an off-line self-adaption adjustment step S2 of adjusting the source CNN vehicle detector obtained in the step S1 in a self-adaption manner, improving the accuracy of the source CNN vehicle detector in a current monitoring scene, and obtaining a target CNN vehicle detector; an on-lien detection step S3 of obtaining a detection image, utilizing the target CNN vehicle detector obtained in the step S2 to carry out the vehicle detection and output a detection result. The method of the present invention adjusts the source CNN vehicle detector based on a convolutional neural network and trained on a large sample in the self-adaption manner and aiming at different monitoring scenes, enables the source CNN vehicle detector to become the target CNN vehicle detector which can finish a vehicle detection task of the current monitoring scene, can detect the vehicles accurately, and possesses the adaptability aiming at the different complicated scenes.

Description

technical field [0001] The invention belongs to the field of computer vision and the field of intelligent transportation technology, in particular to an adaptive vehicle detection method based on a convolutional neural network. Background technique [0002] With the development of video surveillance technology, video cameras have been widely used in various monitoring places. However, the sharp increase in the number of video cameras has caused the traditional manual monitoring methods to be far from meeting the needs of large-scale monitoring. Therefore, intelligent monitoring technology has become the focus of research in the field of computer vision and intelligent transportation technology in recent years. In intelligent monitoring technology, vehicle detection is a key technology, and many subsequent analyzes depend on accurate vehicle detection results. [0003] At present, most vehicle detection methods adopt the traditional detection scheme, that is, firstly, the s...

AI Technical Summary

Problems solved by technology

Although the vehicle detection method based on convolutional neural network has a good detection effect, due to the lack of adaptability to the monitoring scene, when the viewing angle of the monitoring scene changes, the convolutional neural network vehicle trained by this method cannot be used. Detector

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