Method for assisting in learning by pedestrian re-identification feature fusion

Abstract

The invention discloses a method for assisting in learning by pedestrian re-identification feature fusion. The method comprises the following steps that: adopting a global feature extraction model obtained by adding local feature training for extracting the global feature of a pedestrian image, and carrying out pedestrian re-identification by the global feature. The training of the global featureextraction model comprises the following steps that: collecting a whole body image training set, detecting a local image in the whole body image training set, and obtaining a local image training set;independently utilizing the whole body image training set and the local image training set to train a whole body convolutional neural network and a local convolutional neural network to obtain a whole body model and a local model; and independently utilizing the whole body model and the local model to extract the global feature and the local feature of the whole body image training set and the local image training set, and utilizing the global feature which carries out local feature fusion to train the whole body model to obtain a global feature extraction model. By use of the method, duringtraining, the local feature and the global feature are subjected to fusion, and pedestrian re-identification accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and more specifically relates to a method for pedestrian re-identification feature fusion assisted learning. Background technique [0002] When a pedestrian appears under a camera, using the image of the pedestrian under this camera to retrieve images under other cameras is the main task of pedestrian re-identification. Pedestrian re-identification mainly studies how to correctly match images of the same pedestrian target under multiple non-overlapping (disjoint) cameras. In the real surveillance video, due to factors such as changes in viewing angle, changes in pedestrian posture, low resolution of the camera, object occlusion, and changes in illumination, we often cannot obtain high-quality face images, so we cannot use face information for pedestrian reconstruction. identify. Therefore, the research of pedestrian re-identification technology mainly depends on the appearance chara...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above defects or improvement needs of the prior art, the present invention provides a method for pedestrian re-identification feature fusion assisted learning, thereby solving the existing problem in the prior art that only considers learning better global features and local features, but does not consider Technical Issues of Potential Complementary Relationships Between Global and Local Features

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