Streetscape semantic annotation method based on convolutional neural network and semantic transfer conjunctive model

Abstract

The invention relates to a streetscape semantic annotation method based on a convolutional neural network and a semantic transfer conjunctive model. A device according to the streetscape semantic annotation method comprises a deep characteristic extracting part and a soft limited semantic transfer part. A more balanced training set is constructed, and furthermore a super-pixel classification deep model with prior information is trained. According to the streetscape semantic annotation method, the prior information of a scene can be sufficiently mined, and a characteristic expression with more remarkable difference is learned so that the annotation accuracy of a superpixel is greatly improved. Through a Markov random field model, an initial result is optimized and an unnecessary noise is eliminated so that an annotation result is further improved. Finally per-pixel annotation accuracy and average classification accuracy are respectively higher than 77% and 53%.

Description

technical field [0001] The invention belongs to the technical fields of computer vision and graphics processing, and in particular relates to a street view labeling method based on a joint model of convolutional neural network and semantic transfer. Background technique [0002] With the continuous development of the field of intelligent driving, unmanned driving technology has become one of the important directions of research in this field. How to make the computer understand the surrounding environment during the driving of the vehicle and make targeted driving operations is an important research content of driverless cars. The current unmanned driving system uses the integration of traditional technologies such as pedestrian detection, road detection, and traffic sign detection to achieve the purpose of understanding the surrounding street scene, but the effect is not significant. In recent years, researchers have also proposed the method of using street view annotation...

AI Technical Summary

Problems solved by technology

[0007] In order to avoid the problem of unbalanced existing data sets and the inability of existing methods to extract richer and more differentiated target features, this invention proposes a street view semantic labeling method based on a joint model of convolutional neural network and semantic transfer

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