A Street View Image Retrieval Method Based on Fusion of Multiple Features

Abstract

In view of the difficulty in extracting the key area features of the image and the over-complex training in current street view image retrieval methods, this paper proposes a retrieval method that extracts and integrates multiple global features. First, the Convolutional Neural Network is used to extract the features, and then the new multi-scale pooling layer is used to output multiple global features, and the feature loss is reduced by outputting fixed-dimensional features. Finally, the final feature obtained by concatenating multiple global features is used for retrieval. Experimental results show that this method can effectively extract image features, reduce the complexity of training, and improve the accuracy of retrieval.