Pedestrian re-identification method based on improved YOLOv3 network and feature fusion

Abstract

The invention discloses a pedestrian re-identification method based on an improved YOLOv3 network and feature fusion, and mainly solves the problems of low retrieval precision and low speed of specific pedestrians in a video monitoring scene in the prior art. According to the scheme, the method comprises the steps of 1) constructing a pedestrian picture data set; 2) establishing an improved YOLOv3network; 3) establishing a pedestrian re-identification network fusing global features and multi-scale local features; 4) training an improved YOLOv3 network and a pedestrian re-identification network by using the data set; 5) fusing the two networks trained in the step 2) and the step 3) to obtain a pedestrian re-identification system; and 6) inputting the monitoring video and the to-be-retrieved target pedestrian picture into a pedestrian re-identification system, retrieving the to-be-retrieved target pedestrian, and outputting a re-identification result of the target pedestrian. Accordingto the method, the sensitivity to pedestrians with different postures is enhanced, the retrieval speed and precision of pedestrian re-identification are improved, and the method can be used for regional security and protection, criminal investigation, video monitoring and behavior understanding.

Description

technical field [0001] The invention belongs to the field of computer vision, and in particular relates to a pedestrian re-identification method, which can be used for regional security, criminal investigation, video monitoring and behavior understanding. Background technique [0002] In recent years, more and more cameras have been deployed in public places. How to realize the intelligent analysis and application of massive video data with the help of artificial intelligence technology has become the key to building intelligent security. Among them, pedestrian re-identification ReID is one of the core topics. [0003] With the development of face recognition technology, the industry began to seek the possibility of more technical applications. Pedestrian re-identification technology is an important supplement and extension of face technology. More and more Internet giants and technology unicorns are beginning to realize its importance and gradually invest resources in the...

AI Technical Summary

Problems solved by technology

[0006] Traditional pedestrian re-identification methods rely on manual image features, such as color, Haar-like features, histogram HOG, scale-invariant feature transformation SIFT, local binary mode LBP and local maximum occurrence LOMO. These methods ignore the target sensitive area. Susceptible to interference from non-target areas, resulting in reduced detection accuracy and a large amount of computation

Images