Real-time significance pedestrian detection method based on detail discrimination

Abstract

The invention discloses a real-time significance pedestrian detection method based on detail discrimination. The method includes: carrying out parameter pre-training in an existing image data set; reading video data in the monitoring video and converting the video data into a processible image format; performing feature extraction on the image in the step B; and migrating the pre-trained model parameters to a YOLO neural network model, performing network model training on a pedestrian detection data set, and performing pedestrian detection by using the trained network model according to the pedestrian feature H and the saliency feature. Parameter pre-training is carried out on an existing public image data set and is introduced into a YOLO neural network model; pedestrian features are distinguished according to detection significance area features and emphasis details, then pedestrians are detected in real time; and compared with the method that a YOLO model is purely utilized, the multi-scale prediction generalization ability of the model is effectively improved, the detection rate of the system is greatly increased, and the omission ratio is reduced.

Description

technical field

[0001] The invention relates to the field of pedestrian detection, in particular to a real-time significant pedestrian detection method based on detail discrimination. Background technique

[0002] Pedestrian detection is an important research direction in the field of computer vision, which detects whether there are pedestrians in the image by analyzing the image. It has a wide range of applications in the fields of vehicle assisted driving, intelligent monitoring, and intelligent robots. For example, the vehicle auxiliary driving system can use pedestrian detection technology to detect pedestrians in front of the vehicle and remind the driver to avoid; the intelligent monitoring system can use pedestrian detection technology to detect pedestrians in the monitoring screen, so as to analyze the behavior of pedestrians and track suspicious persons; Intelligent robots can use pedestrian detection technology to find pedestrians in the surrounding environment, s...

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