A Pedestrian Search Method and Device Based on Prior Candidate Box Selection Strategy

Abstract

The invention discloses a pedestrian search method and device based on a priori candidate frame selection strategy. The method includes: constructing pedestrian candidate frame feature vectors according to the length and width of all pedestrian bounding boxes in the training set, including two elements of aspect ratio and length; selecting the initial cluster center by k-means++ algorithm; using k-means algorithm to Iterative clustering to obtain the prior candidate frames after clustering; input the pedestrian images in the training set into the predefined pedestrian search network, use the prior candidate frames to generate candidate pedestrians and identify pedestrians, and obtain trained pedestrians through training Search the network; pass the pedestrian probe and the surveillance scene image through the trained pedestrian search network to obtain the characteristics of the pedestrian probe and the characteristics of the candidate pedestrians in the surveillance image, and obtain the surveillance location where the pedestrian probe is located by calculating the similarity of the two features. images and their specific locations. The invention can effectively improve the accuracy and speed of pedestrian search.

Description

technical field [0001] The invention belongs to the field of robot vision technology and intelligent monitoring, and specifically relates to a pedestrian search method and device based on a priori candidate frame selection strategy; by constructing the pedestrian candidate frame feature vector and designing a new distance measurement function, and using the bag of words model to The feature vector clustering of pedestrian candidate frames provides suitable initial candidate frames for pedestrian search, which can further reduce the regression time of pedestrian detection and improve the accuracy of pedestrian recognition in the later stage. Background technique [0002] Pedestrian search is a key technology that simultaneously solves pedestrian detection and pedestrian re-identification, and can be applied to human-computer interaction, intelligent monitoring, and video analysis. However, the performance of the pedestrian detection algorithm is still limited, and the resulti...

AI Technical Summary

Problems solved by technology

However, this method directly migrates the target detection network to pedestrian search, and the target size and pedestrian size in target detection are quite different. Since the two problems themselves have different scenarios, this type of method will introduce a large error

Another way (H.Liu, J.Feng, Z.Jie, K.Jayashree, B.Zhao, M.Qi, J.Jiang and S.Yan, “Neural person search machines,” in IEEE InternationalConference on Computer Vision (ICCV), 2017.) Use the information and attention mechanism of pedestrian probes to continuously match pedestrian probes and monitoring scene images. Compared with the former, the detection accuracy of this method is improved, but its algorithm efficiency is low. Pedestrians need to traverse the entire monitoring scene library, which is not suitable for actual monitoring scenarios

Images