Pedestrian detection method based on deep learning and detection device

Abstract

The invention discloses a pedestrian detection method based on deep learning and a detection device. The method comprises the steps that video data is acquired; multiple key areas where pedestrians possibly exist are positioned according to the video data; the key areas where pedestrians possibly exist are subjected to multiple iterations through a deep convolutional neural network, and pedestrian features after adjustment and filtration are obtained to judge whether pedestrians exist in the key areas; and if pedestrians exist in the key areas, a bonding frame and credibility of each pedestrian detection result are output. When the method is applied to pedestrian detection, the detection effect of the key areas and the detection effect of the pedestrians in the key areas can be improved, the purpose of high-definition video real-time pedestrian detection required by a true application scene is achieved, detection precision and detection efficiency are both improved, and the method is simple and easy to realize.

Description

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AI Technical Summary

Problems solved by technology

[0002] In related technologies, pedestrian detection methods using background modeling and statistical learning may achieve better pedestrian detection efficiency or accuracy under certain conditions, but neither of these two methods can meet the requirements of practical applications

Among them, the background modeling method is generally more complex, resulting in the inability to meet the needs of real-time detection in practical applications, and the method ba

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