A stereoscopic image salience extraction method based on dual-learning network

Abstract

The invention discloses a stereoscopic image visual salience extraction method based on a dual-learning network, which forms a training set of a human gaze map, a left viewpoint color image and a leftparallax image of the stereoscopic image. Then, based on the training set, the depth learning model is constructed by using the feature extraction technology of VGG network model. Secondly, the depthlearning model is trained by using the human gaze map as the monitor and the left viewpoint color image and left parallax image as the input parameters. Then, the left view color image and the left parallax image of the stereoscopic image to be significantly extracted from the vision are taken as input parameters and input into the model obtained from the training to obtain the visually significant image of the stereoscopic image to be significantly extracted from the vision; the advantage is that it can run quickly, and has strong robustness and prediction accuracy.

Description

technical field [0001] The invention relates to a stereoscopic image processing technology, in particular to a method for extracting visual salience of a stereoscopic image based on a double learning network. Background technique [0002] In human visual reception and information processing, due to limited brain resources and differences in the importance of external environmental information, the human brain does not treat external environmental information equally in the processing process, but shows selective characteristics. When people watch images or video clips, their attention is not evenly distributed to every area of ​​the image, but they pay more attention to certain salient areas. How to detect and extract salient regions with high visual attention in videos is an important research content in the field of computer vision and content-based video retrieval. With the rapid development of stereoscopic video display technology and high-quality stereoscopic video con...

AI Technical Summary

Problems solved by technology

[0003] However, a stereoscopic image is not a simple spatial extension of a planar image, so the process of human perception of a stereoscopic image to generate stereoscopic vision is not a simple process of superimposing left-viewpoint images and right-viewpoint images. force) is not a simple extension of the plane visual properties

However, the existing saliency map extraction methods for stereo images are still limited to the simple extension of the saliency extraction methods for planar images.

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